Search results for: hydraulic flume experiments

Authors: Lanchi Xie, Zhihui Li, Zhigang Li, Guiqiang Wang, Lei Xu, Yuwen Yan

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Image-based facial features can be classified into category recognition features and individual recognition features. Current automated face recognition systems extract a specific feature vector of different dimensions from a facial image according to their pre-trained neural network. However, to improve the efficiency of parameter calculation, an algorithm generally reduces the image details by pooling. The operation will overlook the details concerned much by forensic experts. In our experiment, we adopted a variety of face recognition algorithms based on deep learning, compared a large number of naturally collected face images with the known data of the same person's frontal ID photos. Downscaling and manual handling were performed on the testing images. The results supported that the facial recognition algorithms based on deep learning detected structural and morphological information and rarely focused on specific markers such as stains and moles. Overall performance, distribution of genuine scores and impostor scores, and likelihood ratios were tested to evaluate the accuracy of biometric systems and forensic experts. Experiments showed that the biometric systems were skilled in distinguishing category features, and forensic experts were better at discovering the individual features of human faces. In the proposed approach, a fusion was performed at the score level. At the specified false accept rate, the framework achieved a lower false reject rate. This paper contributes to improving the interpretability of the objective method of facial comparison and provides a novel method for human-machine collaboration in this field.

Keywords: likelihood ratio, automated facial recognition, facial comparison, biometrics

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Authors: Arijit Saha, Hassan Kassem, Leo Hoening

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Ongoing climate change demands the increasing use of renewable energies. Wind energy plays an important role in this context since it can be applied almost everywhere in the world. To reduce the costs of wind turbines and to make them more competitive, simulations are very important since experiments are often too costly if at all possible. The wind turbine on a vast open area experiences the turbulence generated due to the atmosphere, so it was of utmost interest from this research point of view to generate the turbulence through various Inlet Turbulence Generation methods like Precursor cyclic and Kaimal Spectrum Exponential Coherence (KSEC) in the computational simulation domain. To be able to validate computational fluid dynamic simulations of wind turbines with the experimental data, it is crucial to set up the conditions in the simulation as close to reality as possible. This present work, therefore, aims at investigating the turbulent inflow strategy and boundary conditions of KSEC and providing a comparative analysis alongside the Precursor cyclic method for Large Eddy Simulation within the context of wind energy applications. For the generation of the turbulent box through KSEC method, firstly, the constrained data were collected from an auxiliary channel flow, and later processing was performed with the open-source tool PyconTurb, whereas for the precursor cyclic, only the data from the auxiliary channel were sufficient. The functionality of these methods was studied through various statistical properties such as variance, turbulent intensity, etc with respect to different Bulk Reynolds numbers, and a conclusion was drawn on the feasibility of KSEC method. Furthermore, it was found necessary to verify the obtained data with DNS case setup for its applicability to use it as a real field CFD simulation.

Keywords: Inlet Turbulence Generation, CFD, precursor cyclic, KSEC, large Eddy simulation, PyconTurb

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Authors: Svetlana Guryeva, Inna Kornienko, Elena Petersen

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At present, translational medicine is a rapidly developing branch of biomedicine. The main idea of translational medicine is a practical application of fundamental research. One of the possible applications for translational medicine is researching therapies that improve human age-related organism condition. To fill the gap between experiments and clinical practice, it is necessary to create the standardized system for the investigation of different effects on cellular aging models. In this study, primary human fibroblasts derived from patients of different ages were used as a cellular aging model. The senescence-associated β-galactosidase activity, lipofuscin, γ-H2AX, the reactive oxygen species level, and cell death markers (annexin V/propidium iodide) were used as biomarkers of the cell functional state. The effects of damaging exposures (oxidative stress and heat shock), potential positive factors (metformin and acetaminophen), and their combinations were investigated using the described biomarkers. Oxidative stress and heat shock caused the increase in the levels of all biomarkers, and only the cells from young patients partly coped with stress 3 days after the exposures. Metformin improved the state of pretreatment cells from young and old patients. The acetaminophen did not show significant changes in the biomarker levels compare to the action of metformin. This study proved the opportunity to develop a standardized screening system based on biomarkers of the cell functional state to identify potential positive or negative effects of some physical and chemical exposures. Moreover, such a system can be useful for the aims of regenerative medicine to determine the effect of cell pretreatment before transplantation.

Keywords: biomarkers, primary fibroblasts, regenerative medicine, senescence, test system, translational medicine

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Authors: Anna Yagodnitsyna, Alexander Kovalev, Artur Bilsky

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The efficiency of certain technological processes in two-phase microfluidics such as emulsion production, nanomaterial synthesis, nitration, extraction processes etc. depends on two-phase flow regimes in microchannels. For practical application in chemistry and biochemistry it is very important to predict the expected flow pattern for a large variety of fluids and channel geometries. In the case of immiscible liquids, the plug flow is a typical and optimal regime for chemical reactions and needs to be predicted by empirical data or correlations. In this work flow patterns of immiscible liquid-liquid flow in a rectangular microchannel with T-junction are investigated. Three liquid-liquid flow systems are considered, viz. kerosene – water, paraffin oil – water and castor oil – paraffin oil. Different flow patterns such as parallel flow, slug flow, plug flow, dispersed (droplet) flow, and rivulet flow are observed for different velocity ratios. New flow pattern of the parallel flow with steady wavy interface (serpentine flow) has been found. It is shown that flow pattern maps based on Weber numbers for different liquid-liquid systems do not match well. Weber number multiplied by Ohnesorge number is proposed as a parameter to generalize flow maps. Flow maps based on this parameter are superposed well for all liquid-liquid systems of this work and other experiments. Plug length and velocity are measured for the plug flow regime. When dispersed liquid wets channel walls plug length cannot be predicted by known empirical correlations. By means of particle tracking velocimetry technique instantaneous velocity fields in a plug flow regime were measured. Flow circulation inside plug was calculated using velocity data that can be useful for mass flux prediction in chemical reactions.

Keywords: flow patterns, hydrodynamics, liquid-liquid flow, microchannel

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Authors: Jiang Xu, Daoping Wang, Yinghong Pan

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The jointing-booting stage is a critical period of both vegetative growth and reproductive growth in rice. Therefore, the proteomic analysis of the mutant Osbri1, whose corresponding gene OsBRI1 encodes the putative BRs receptor OsBRI1, at jointing-booting stage is very important for understanding the effects of BRs on vegetative and reproductive growth. In this study, the proteomes of leaves from an allelic mutant of the DWARF 61 (D61, OsBRI1) gene, Fn189 (dwarf54, d54) and its wild-type variety T65 (Taichung 65) at jointing-booting stage were analysed by using a Q Exactive plus orbitrap mass spectrometer, and more than 3,100 proteins were identified in each sample. Ontology analysis showed that these proteins distribute in various space of the cells, such as the chloroplast, mitochondrion, and nucleus, they functioned as structural components and/or catalytic enzymes and involved in many physiological processes. Moreover, quantitative analysis displayed that 266 proteins were differentially expressed in two samples, among them, 77 proteins decreased and 189 increased more than two times in Fn189 compared with T65, the proteins whose content decreased in Fn189 including b5-like Heme/Steroid binding domain containing protein, putative retrotransposon protein, putative glutaminyl-tRNA synthetase, and higher content proteins such as mTERF, putative Oligopeptidase homologue, zinc knuckle protein, and so on. A former study founded that the transcription level of a mTERF was up-regulated in the leaves of maize seedling after EBR treatment. In our experiments, it was interesting that one mTERF protein increased, but another mTERF decreased in leaves of Fn189 at jointing-booting stage, which suggested that BRs may have differential regulation mechanisms on the expression of various mTERF proteins. The relationship between other differential proteins with BRs is still unclear, and the effects of BRs on rice protein contents and its regulation mechanisms still need further research.

Keywords: bri1 mutant, jointing-booting stage, proteomic analysis, rice

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Authors: K. S. Zaytsev, Y. R. Nartsissov

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Glycine is one of the key inhibitory neurotransmitters in Central nervous system (CNS) meanwhile glycinergic transmission is highly dependable on its appropriate reuptake from synaptic cleft. Glycine transporters (GlyT) of types 1 and 2 are the enzymes providing glycine transport back to neuronal and glial cells along with Na⁺ and Cl⁻ co-transport. The distribution and stoichiometry of GlyT1 and GlyT2 differ in details, and GlyT2 is more interesting for the research as it reuptakes glycine to neuron cells, whereas GlyT1 is located in glial cells. In the process of GlyT2 activity, the translocation of the amino acid is accompanied with binding of both one chloride and three sodium ions consequently (two sodium ions for GlyT1). In the present study, we developed a computer simulator of GlyT2 and GlyT1 activity based on known experimental data for quantitative estimation of membrane glycine transport. The trait of a single protein functioning was described using the probability approach where each enzyme state was considered separately. Created scheme of transporter functioning realized as a consequence of elemental steps allowed to take into account each event of substrate association and dissociation. Computer experiments using up-to-date kinetic parameters allowed receiving the number of translocated glycine molecules, Na⁺ and Cl⁻ ions per time period. Flexibility of developed software makes it possible to evaluate glycine reuptake pattern in time under different internal characteristics of enzyme conformational transitions. We investigated the behavior of the system in a wide range of equilibrium constant (from 0.2 to 100), which is not determined experimentally. The significant influence of equilibrium constant in the range from 0.2 to 10 on the glycine transfer process is shown. The environmental conditions such as ion and glycine concentrations are decisive if the values of the constant are outside the specified range.

Keywords: glycine, inhibitory neurotransmitters, probability approach, single protein functioning

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Authors: Enlin Lo, Ioannis Dogaris, George Philippidis

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Succinic acid is a compound used for manufacturing lacquers, resins, and other coating chemicals. It is also used in the food and beverage industry as a flavor additive. It is predominantly manufactured from petrochemicals, but it can also be produced by fermentation of sugars from renewable feedstocks, such as plant biomass. Bio-based succinic acid has great potential in becoming a platform chemical (building block) for commodity and high-value chemicals. In this study, the production of bio-based succinic acid from sweet sorghum was investigated. Sweet sorghum has high fermentable sugar content and can be cultivated in a variety of climates. In order to avoid competition with food feedstocks, its non-edible ‘bagasse’ (the fiber part after extracting the juice) was targeted. Initially, various conditions of pretreating sweet sorghum bagasse (SSB) were studied in an effort to remove most of the non-fermentable components and expose the cellulosic fiber containing the fermentable sugars (glucose). Concentrated (83%) phosphoric acid was utilized at temperatures 50-80 oC for 30-60 min at various SSB loadings (10-15%), coupled with enzymatic hydrolysis using commercial cellulase (Ctec2, Novozymes) enzyme, to identify the conditions that lead to the highest glucose yields for subsequent fermentation to succinic acid. As the pretreatment temperature and duration increased, the bagasse color changed from light brown to dark brown-black, indicating decomposition, which ranged from 15% to 72%, while the theoretical glucose yield is 91%. With Minitab software statistical analysis, a model was built to identify the optimal pretreatment condition for maximum glucose released. The projected theoretical bio-based succinic acid production is 23g per 100g of SSB, which will be confirmed with fermentation experiments using the bacterium Actinobacillus succinogenes.

Keywords: biomass, cellulose, enzymatic hydrolysis, fermentation, pretreatment, succinic acid

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Authors: Jaehong Yu, Seoung Bum Kim

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Clustering analysis can facilitate the extraction of intrinsic patterns in a dataset and reveal its natural groupings without requiring class information. For effective clustering analysis in high dimensional datasets, unsupervised dimensionality reduction is an important task. Unsupervised dimensionality reduction can generally be achieved by feature extraction or feature selection. In many situations, feature selection methods are more appropriate than feature extraction methods because of their clear interpretation with respect to the original features. The unsupervised feature selection can be categorized as feature subset selection and feature ranking method, and we focused on unsupervised feature ranking methods which evaluate the features based on their importance scores. Recently, several unsupervised feature ranking methods were developed based on ensemble approaches to achieve their higher accuracy and stability. However, most of the ensemble-based feature ranking methods require the true number of clusters. Furthermore, these algorithms evaluate the feature importance depending on the ensemble clustering solution, and they produce undesirable evaluation results if the clustering solutions are inaccurate. To address these limitations, we proposed an ensemble-based feature ranking method with random subspace and multiple-k ensemble (FRRM). The proposed FRRM algorithm evaluates the importance of each feature with the random subspace ensemble, and all evaluation results are combined with the ensemble importance scores. Moreover, FRRM does not require the determination of the true number of clusters in advance through the use of the multiple-k ensemble idea. Experiments on various benchmark datasets were conducted to examine the properties of the proposed FRRM algorithm and to compare its performance with that of existing feature ranking methods. The experimental results demonstrated that the proposed FRRM outperformed the competitors.

Keywords: clustering analysis, multiple-k ensemble, random subspace-based feature evaluation, unsupervised feature ranking

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Authors: Francisco Javier Montes Ruiz-Cabello, Guillermo Guerrero-Vacas, Sara Bermudez-Romero, Miguel Cabrerizo Vilchez, Miguel Angel Rodriguez-Valverde

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Galvanized steel is one of the widespread metallic materials used in industry. It consists on a iron-based alloy (steel) coated with a layer of zinc with variable thickness. The zinc is aimed to prevent the inner steel from corrosion and staining. Its production is cheaper than the stainless steel and this is the reason why it is employed in the construction of materials with large dimensions in aeronautics, urban/ industrial edification or ski-resorts. In all these applications, turning the natural hydrophilicity of the metal surface into superhydrophobicity is particularly interesting and would open a wide variety of additional functionalities. However, producing a superhydrophobic surface on galvanized steel may be a very difficult task. Superhydrophobic surfaces are characterized by a specific surface texture which is reached either by coating the surface with a material that incorporates such texture, or by conducting several roughening methods. Since galvanized steel is already a coated material, the incorporation of a second coating may be undesired. On the other hand, the methods that are recurrently used to incorporate the surface texture leading to superhydrophobicity in metals are aggressive and may damage their surface. In this work, we used a novel strategy which goal is to produce superhydrophobic galvanized steel by a two-step non-aggressive process. The first process is aimed to create a hierarchical structure by incorporating zinc nanoparticles sintered on the surface at a temperature slightly lower than the zinc’s melting point. The second one is a hydrophobization by a thick fluoropolymer layer deposition. The wettability of the samples is characterized in terms of tilting plate and bouncing drop experiments, while the roughness is analyzed by confocal microscopy. The durability of the produced surfaces was also explored.

Keywords: galvanaized steel, superhydrophobic surfaces, sintering nanoparticles, zinc nanopowder

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Authors: Zhiguo Yang, Xiangan Yue, Minglu Shao, Yue Yang, Rongjie Yan

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It is difficult to realize deep profile control because of the small pore-throats and easy water channeling in low-permeability heterogeneous reservoir, and the traditional polymer microspheres have the contradiction between injection and plugging. In order to solve this contradiction, the controllable self-aggregating colloidal particles (CSA) containing amide groups on the surface of microspheres was prepared based on emulsion polymerization of styrene and acrylamide. The dispersed solution of CSA colloidal particles, whose particle size is much smaller than the diameter of pore-throats, was injected into the reservoir. When the microspheres migrated to the deep part of reservoir, , these CSA colloidal particles could automatically self-aggregate into large particle clusters under the action of the shielding agent and the control agent, so as to realize the plugging of the water channels. In this paper, the morphology, temperature resistance and self-aggregation properties of CSA microspheres were studied by transmission electron microscopy (TEM) and bottle test. The results showed that CSA microspheres exhibited heterogeneous core-shell structure, good dispersion, and outstanding thermal stability. The microspheres remain regular and uniform spheres at 100℃ after aging for 35 days. With the increase of the concentration of the cations, the self-aggregation time of CSA was gradually shortened, and the influence of bivalent cations was greater than that of monovalent cations. Core flooding experiments showed that CSA polymer microspheres have good injection properties, CSA particle clusters can effective plug the water channels and migrate to the deep part of the reservoir for profile control.

Keywords: heterogeneous reservoir, deep profile control, emulsion polymerization, colloidal particles, plugging characteristic

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Authors: Yubo Bi, Xiao Chen, Shouxiang Lu

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

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

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Authors: Leizhang Wang, Baocang Wang

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General Sieve Kernel (G6K) is considered as currently the fastest algorithm for the shortest vector problem (SVP) and record holder of open SVP challenge. We study the lattice basis quality improvement effects of the Workout proposed in G6K, which is composed of a series of pumps to solve SVP. Firstly, we use a low-dimensional pump output basis to propose a predictor to predict the quality of high-dimensional Pumps output basis. Both theoretical analysis and experimental tests are performed to illustrate that it is more computationally expensive to solve the LWE problems by using a G6K default SVP solving strategy (Workout) than these lattice reduction algorithms (e.g. BKZ 2.0, Progressive BKZ, Pump, and Jump BKZ) with sieving as their SVP oracle. Secondly, the default Workout in G6K is optimized to achieve a stronger reduction and lower computational cost. Thirdly, we combine the optimized Workout and the Pump output basis quality predictor to further reduce the computational cost by optimizing LWE instances selection strategy. In fact, we can solve the TU LWE challenge (n = 65, q = 4225, = 0:005) 13.6 times faster than the G6K default Workout. Fourthly, we consider a combined two-stage (Preprocessing by BKZ- and a big Pump) LWE solving strategy. Both stages use dimension for free technology to give new theoretical security estimations of several LWE-based cryptographic schemes. The security estimations show that the securities of these schemes with the conservative Newhope’s core-SVP model are somewhat overestimated. In addition, in the case of LAC scheme, LWE instances selection strategy can be optimized to further improve the LWE-solving efficiency even by 15% and 57%. Finally, some experiments are implemented to examine the effects of our strategies on the Normal Form LWE problems, and the results demonstrate that the combined strategy is four times faster than that of Newhope.

Keywords: LWE, G6K, pump estimator, LWE instances selection strategy, dimension for free

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Authors: T. Yılmaz, Ş. Tavman

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In this study, optimization of ultrasound assisted extraction (UAE) of hemicellulose based polysaccharides from plant waste material has been studied. Selected material is hazelnut skin. Extraction variables for the operation are extraction time, amplitude and application temperature. Optimum conditions have been evaluated depending on responses such as amount of wet crude polysaccharide, total carbohydrate content and dried sample. Pretreated hazelnut skin powders were used for the experiments. 10 grams of samples were suspended in 100 ml water in a jacketed vessel with additional magnetic stirring. Mixture was sonicated by immersing ultrasonic probe processor. After the extraction procedures, ethanol soluble and insoluble sides were separated for further examinations. The obtained experimental data were analyzed by analysis of variance (ANOVA). Second order polynomial models were developed using multiple regression analysis. The individual and interactive effects of applied variables were evaluated by Box Behnken Design. The models developed from the experimental design were predictive and good fit with the experimental data with high correlation coefficient value (R2 more than 0.95). Extracted polysaccharides from hazelnut skin are assumed to be pectic polysaccharides according to the literature survey of Fourier Transform Spectrometry (FTIR) analysis results. No more change can be observed between spectrums of different sonication times. Application of UAE at optimized condition has an important effect on extraction of hemicellulose from plant material by satisfying partial hydrolysis to break the bounds with other components in plant cell wall material. This effect can be summarized by varied intensity of microjets and microstreaming at varied sonication conditions.

Keywords: hazelnut skin, optimization, polysaccharide, ultrasound assisted extraction

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Authors: Nazia Zaffar, Alam Khan, Abdul Haq, Malik Badshah

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Pakistan is an agricultural country. The increasing population leads to an increase in demand for food. A large number of crops are infected by different microbes, and nutrient deficiency of soil adversely affects the yield of crops. Furthermore, the use of chemical fertilizers like Nitrogen, Phosphorus, Potassium (NPK) Urea, and Diammonium phosphate (DAP) and pesticides have environmental consequences. Therefore, there is an urgent need to explore alternative renewable and sustainable biofertilizers. Maize is one of the top growing crops in Pakistan, but it has low yield compared to other countries due to deficiency of organic matter, widespread nutrients deficiency (phosphorus and nitrogen), unbalanced use of fertilizers and various fungal diseases. In order to get rid of all these disadvantages, Digestate emerged as a win-win opportunity for the control of a few plant diseases and a replacement for the chemical fertilizers. The present study was designed to investigate the effect of Anerobic digestate on Antifungal Activity and in different parameters of Maize. The antifungal activity, minimum inhibitory concentration (MIC), and minimum fungicidal concentration (MFC) against selected phytopathogens (Colletotrichum coccodis, Pythium ultimum, Phytophthora capsci, Rhizoctonia solani, Bipolaris oryzae and Fusarium Fujikuroi) were determined by microtiter plate method. The effect of various fertilizers in different growth parameters height, diameter, chlorophyll, leaf area, biomass, and yield were studied in field experiments. The extracts from anaerobic digestate have shown antifungal activity against selected phytopathogens, the highest activity was noted against P. ultimum, the MIC activity was high in case of P. ultimum and B. oryzae. The present study concludes that anaerobic digestate have a positive effect on maize growth and yield as well as an antifungal activity which can be potentially a good biofertilizer.

Keywords: anaerobic digestate, antifungal activity, MIC, phytopathogens

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Authors: Fangyuan Shao, Wei Liu, Deli Gao

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Polycrystalline diamond compact (PDC) bits have occupied a large market of unconventional oil and gas drilling. The application of PDC bits benefits from the efficient rock breaking of PDC cutters. In response to increasingly complex formations, many shaped cutters have been invited, but many of them have not been solved by the mechanism of rock breaking. In this paper, two kinds of PDC cutters: a new axe-shaped (NAS) cutter and cylindrical cutter (benchmark) were studied by laboratory experiments. NAS cutter is obtained by optimizing two sides of axe-shaped cutter with curved surfaces. All the cutters were put on a vertical turret lathe (VTL) in the laboratory for cutting tests. According to the cutting distance, the VTL tests can be divided into two modes: single-turn rotary cutting and continuous cutting. The cutting depth of cutting (DOC) was set at 1.0 mm and 2.0 mm in the former mode. The later mode includes a dry VTL test for thermal stability and a wet VTL test for wear resistance. Load cell and 3D optical profiler were used to obtain the value of cutting forces and wear area, respectively. Based on the findings of the single-turn rotary cutting VTL tests, the performance of A NAS cutter was better than the benchmark cutter on elastoplastic material cutting. The cutting forces (normal forces, tangential force, and radial force) and special mechanical energy (MSE) of a NAS cutter were lower than that of the benchmark cutter under the same condition. It meant that a NAS cutter was more efficient on elastoplastic material breaking. However, the wear resistance of a new axe-shaped cutter was higher than that of a benchmark cutter. The results of the dry VTL test showed that the thermal stability of a NAS cutter was higher than that of a benchmark cutter. The cutting efficiency can be improved by optimizing the geometric structure of the PDC cutter. The change of thermal stability may be caused by the decrease of the contact area between cutter and rock at given DOC. The conclusions of this paper can be used as an important reference for PDC cutters designers.

Keywords: axe-shaped cutter, PDC cutter, rotary cutting test, vertical turret lathe

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Authors: Pawthawala Nancy Manish, Syed Alay Hashim

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A hybrid rocket is a rocket engine which uses propellants in two different states of matter- one is in solid and the other either gas or liquid. A hybrid rocket exhibit advantages over both liquid rockets and solid rockets especially in terms of simplicity, stop-start-restart capabilities, safety and cost. This paper deals the design and development of a hybrid rocket having paraffin wax as solid fuel and liquid oxygen as oxidizer. Due to variation of pressure in combustion chamber there is significantly change in mass flow rate, burning rate and uneven regression along the length of the grain. This project describes the working model of a hybrid propellant rocket motor. We have designed a hybrid rocket thrust chamber based on the predetermined combustion chamber pressure and the properties of hybrid propellant. This project is all ready in working condition with normal oxygen injector. Now we have planned to modify the injector design to improve the combustion property. We will use spray type injector for injecting the oxidizer. This idea will increase the performance followed by the regression rate of the solid fuel. By employing mass conservation law, oxygen mass flux, oxidizer/fuel ratio and regression rate the thrust coefficient can be obtained for our current design. CATIA V5 R20 is our design software for the complete setup. This project is fully based on experimental evaluation and the collection of combustion and flow parameters. The thrust chamber is made of stainless steel and the duration of test is around 15-20 seconds (Maximum). These experiments indicates that paraffin based fuel provides the opportunity to satisfy a broad range of mission requirements for the next generation of the hybrid rocket system.

Keywords: burning rate, liquid oxygen, mass flow rate, paraffin wax and sugar

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Authors: Sarah Gaßmeyer, Nadine Hülsemann, Raphael Stoll, Kenji Miyamoto, Robert Kourist

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Enzymatic racemization allows the smooth interconversion of stereocenters under very mild reaction conditions. Racemases find frequent applications in deracemization and dynamic kinetic resolutions. Arylmalonate decarboxylase (AMDase) from Bordetella Bronchiseptica has high structural similarity to amino acid racemases. These cofactor-free racemases are able to break chemically strong CH-bonds under mild conditions. The racemase-like catalytic machinery of mutant G74C conveys it a unique activity in the racemisation of pharmacologically relevant derivates of 2-phenylpropionic acid (profenes), which makes AMDase G74C an interesting object for the mechanistic investigation of cofactor-independent racemases. Structure-guided protein engineering achieved a variant of this unique racemase with 40-fold increased activity in the racemisation of several arylaliphatic carboxylic acids. By saturation–transfer–difference NMR spectroscopy (STD-NMR), substrate binding during catalysis was investigated. All atoms of the substrate showed interactions with the enzyme. STD-NMR measurements revealed distinct nuclear Overhauser effects in experiments with and without molecular conversion. The spectroscopic analysis led to the identification of several amino acid residues whose variation increased the activity of G74C. While single-amino acid exchanges increased the activity moderately, structure-guided saturation mutagenesis yielded a quadruple mutant with a 40 times higher reaction rate. This study presents STD-NMR as versatile tool for the analysis of enzyme-substrate interactions in catalytically competent systems and for the guidance of protein engineering.

Keywords: racemase, rational protein design, STD-NMR, structure guided saturation mutagenesis

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Authors: Danute Jablonskyte-Rasce, Laura Masilionyte

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The field experiments of different farming systems were conducted at Joniškėlis Experimental Station of the Lithuanian Research Centre for Agriculture and Forestry in 2006–2016. The soil of the experimental site was Endocalcari-Endohypogleyic Cambisol (CMg-n-w-can). The research was designed to identify the effects of dry matter and nitrogen accumulated in the above-ground biomass of various catch crops grown after winter wheat on soil mineral nitrogen variation during the autumn and spring period in the presence of intensive leaching complex. Research was done in the soil differing in humus status in the organic and sustainable cropping systems by growing various plant mixtures as catch crops: narrow-leafed lupine (Lupinus angustifolius L.) and oil radish (Raphanus sativus var. Oleifera L.), white mustard (Sinapis alba L.) and buckwheat (Fagopyrum exculentum Moench.) and white mustard as a sole crop. All crop and soil management practices have shown optimal efficiency in late autumn – stubble breaking, catch crops and straw used during the post-harvest period of the main crops, reduced Nmin migration into deeper (40–80 cm) soil layer. The greatest Nmin reduction in the 0–40 cm soil layer during the period from late autumn to early spring was identified in the sustainable cropping system having applied N30 for the promotion of straw mineralization and with no catch crops cultivation. The sustainable cropping system, having applied N30 for straw mineralization and growing white mustard in combination with buckwheat as catch crops, Nmin difference in the spring compared with its status in the autumn in the soil low and moderate in humus was lower by 70.1% and 34.2%, respectively.

Keywords: soil nitrogen, catch crops, ecological and sustainable farming systems, Cambisol

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Authors: Girmaye Abebe, Brook Lemma

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Adsorption of phosphorus (P as PO43-) in filter cake was studied to assess the media's capability in removing phosphorous from wastewaters. The composition of the filter cake that was generated from alum manufacturing process as waste residue has high amount of silicate from the complete silicate analysis of the experiment. Series of batches adsorption experiments were carried out to evaluate parameters that influence the adsorption capacity of PO43-. The factors studied include the effect of contact time, adsorbent dose, thermal pretreatment of the adsorbent, neutralization of the adsorbent, initial PO43- concentration, pH of the solution and effect of co-existing anions. Results showed that adsorption of PO43- is fairly rapid in first 5 min and after that it increases slowly to reach the equilibrium in about 1 h. The treatment efficiency of PO43- was increased with adsorbent extent. About 90% removal efficiency was increased within 1 h at an optimum adsorbent dose of 10 g/L for initial PO43- concentration of 10 mg/L. The amount of PO43- adsorbed increased with increasing initial PO43- concentration. Heat treatment and surface neutralization of the adsorbent did not improve the PO43- removal capacity and efficiency. The percentage of PO43- removal remains nearly constant within the pH range of 3-8. The adsorption data at ambient pH were well fitted to the Langmuir Isotherm and Dubinin–Radushkevick (D–R) isotherm model with a capacity of 25.84 and 157.55 mg/g of the adsorbent respectively. The adsorption kinetic was found to follow a pseudo-second-order rate equation with an average rate constant of 3.76 g.min−1.mg−1. The presence of bicarbonate or carbonate at higher concentrations (10–1000 mg/L) decreased the PO43- removal efficiency slightly while other anions (Cl-, SO42-, and NO3-) have no significant effect within the concentration range tested. The overall result shows that the filter cake is an efficient PO43- removing adsorbent against many parameters.

Keywords: wastewater, filter cake, adsorption capacity, phosphate (PO43-)

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Authors: Y. Trantafyllou, C. Alexandraki

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Music interpretation accounts to the way musicians shape their performance by deliberately deviating from composers’ intentions, which are commonly communicated via some form of music transcription, such as a music score. For transcribed and non-improvised music, music expression is manifested by introducing subtle deviations in tempo, dynamics and articulation during the evolution of performance. This paper presents an application, named FlameCens, which, given two recordings of the same piece of music, presumably performed by different musicians, allow visualising deviations in tempo and dynamics during playback. The application may also compare a certain performance to the music score of that piece (i.e. MIDI file), which may be thought of as an expression-neutral representation of that piece, hence depicting the expressive queues employed by certain performers. FlameCens uses the Dynamic Time Warping algorithm to compare two audio sequences, based on CENS (Chroma Energy distribution Normalized Statistics) audio features. Expressive deviations are illustrated in a moving flame, which is generated by an animation of particles. The length of the flame is mapped to deviations in dynamics, while the slope of the flame is mapped to tempo deviations so that faster tempo changes the slope to the right and slower tempo changes the slope to the left. Constant slope signifies no tempo deviation. The detected deviations in tempo and dynamics can be additionally recorded in a text file, which allows for offline investigation. Moreover, in the case of monophonic music, the color of particles is used to convey the pitch of the notes during performance. FlameCens has been implemented in Python and it is openly available via GitHub. The application has been experimentally validated for different music genres including classical, contemporary, jazz and popular music. These experiments revealed that FlameCens can be a valuable tool for music specialists (i.e. musicians or musicologists) to investigate the expressive performance strategies employed by different musicians, as well as for music audience to enhance their listening experience.

Keywords: audio synchronization, computational music analysis, expressive music performance, information visualization

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Authors: Changyeop Lee, Sewon Kim, Jongho Lee

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Reburning technology has been developed to adopt various commercial combustion systems. Fuel lean reburning is an advanced reburning method to reduce NOx economically without using burnout air, however it is not easy to get high NOx reduction efficiency. In the fuel lean reburning system, the localized fuel rich eddies are used to establish partial fuel rich regions so that the NOx can react with hydrocarbon radical restrictively. In this paper, a new advanced reburning method which supplies reburn fuel with oscillatory motion is introduced to increase NOx reduction rate effectively. To clarify whether forced oscillating injection of reburn fuel can effectively reduce NOx emission, experimental tests were conducted in vertical combustion furnace. Experiments were performed in flames stabilized by a gas burner, which was mounted at the bottom of the furnace. The natural gas is used as both main and reburn fuel and total thermal input is about 40kW. The forced oscillating injection of reburn fuel is realized by electronic solenoid valve, so that fuel rich region and fuel lean region is established alternately. In the fuel rich region, NOx is converted to N2 by reburning reaction, however unburned hydrocarbon and CO is oxidized in fuel lean zone and mixing zone at downstream where slightly fuel lean region is formed by mixing of two regions. This paper reports data on flue gas emissions and temperature distribution in the furnace for a wide range of experimental conditions. All experimental data has been measured at steady state. The NOx reduction rate increases up to 41% by forced oscillating reburn motion. The CO emissions were shown to be kept at very low level. And this paper makes clear that in order to decrease NOx concentration in the exhaust when oscillating reburn fuel injection system is adopted, the control of factors such as frequency and duty ratio is very important.

Keywords: NOx, CO, reburning, pollutant

Procedia PDF Downloads 267

Authors: Pabasara H. Gamage, Sisira K. Weliwegamage, Sameera R. Gunatilake, Hondamuni I. C De Silva, Parakrama Karunaratne

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Green diesel is an upcoming category of biofuels, which has more practical advantages than biodiesel. Production of green diesel involves production of hydrocarbons from various fatty acid sources. Though green diesel is chemically similar to fossil fuel hydrocarbons, it is more environmentally friendly. Decarboxylation of fatty acid sources is one of green diesel production methods and is less expensive and more energy efficient compared to hydrodeoxygenation. Free fatty acids (FFA), undergo decarboxylation readily than triglycerides. Waste coconut oil, which is a rich source of FFA, can be easily decarboxylated than other oils which have lower FFA contents. These free fatty acids can be converted to hydrocarbons by decarboxylation. Experiments were conducted to carry out decarboxylation of waste coconut oil in a high pressure hastealloy reactor (Toption Goup LTD), in the presence of soda lime and mixtures of soda lime and alumina. Acid value (AV) correlates to the amount of FFA available in a sample of oil. It can be shown that with the decreasing of AV, FFAs have converted to hydrocarbons. First, waste coconut oil was reacted with soda lime alone, at 150 °C, 200 °C, and 250 °C and 1.2 MPa pressure for 2 hours. AVs of products at different temperatures were compared. AV of products decreased with increasing temperature. Thereafter, different mixtures of soda lime and alumina (100% Soda lime, 1:1 soda lime and alumina and 100% alumina) were employed at temperatures 150 °C, 200 °C, and 250 °C and 1.2 MPa pressure. The lowest AV of 2.99±0.03 was obtained when 1:1 soda lime and alumina were employed at 250 °C. It can be concluded with respect to the AV that the amount of FFA decreased when decarboxylation temperature was increased. Soda lime:alumina 1:1 mixture showed the lowest AV among the compositions studied. These findings lead to formulate a method to successfully synthesize hydrocarbons by decarboxylating waste coconut oil in the presence of soda lime and alumina (1:1) at elevated tempertaures such as 250 °C.

Keywords: acid value, free fatty acids, green diesel, high pressure reactor, waste coconut oil

Procedia PDF Downloads 275

Authors: Kashan Bashir, Salah Naji Ahmed Sufyan, Mirza Umar Baig

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In this study, n-dodecane, tetralin, decalin, and tetramethybenzene (TMBE) were used as model compounds of alkanes, naphthenic-aromatic, cycloalkanes and alkyl-benzenes presented in hydro-diesel. The catalytic cracking properties of four model compounds over Y zeolite catalyst (Y-Cat.) and ZSM-5 zeolite catalysts (ZSM-5-Cat.) were probed. The experiment results revealed that high conversion of macromolecular paraffin and naphthenic aromatics were achieved over Y-Cat, whereas its low cracking activity of intermediate products micromolecules paraffin and olefin and high activity of hydride transfer reaction goes against the production of value-added products (light olefin and gasoline). In contrast, despite the fact that the hydride transfer reaction was greatly inhabited over ZSM-5-Cat, the low conversion of macromolecules was observed attributed to diffusion limitations. Interestingly, the mixed catalyst compensates for the shortcomings of the two catalysts, and a “relay reaction” between Y-Cat and ZSM-5-Cat was proposed. Specifically, the added Y-Cat acts as a “pre-cracking booster site” and promotes macromolecules conversion. The addition of ZSM-5-Cat not only significantly suppresses the hydride transfer reaction but also contributes to the cracking of immediate products paraffin and olefin into ethylene and propylene, resulting in a high yield of alkyl-benzene (gasoline), ethylene, and propylene with a low yield of naphthalene (LCO) and coke. The catalytic cracking evaluation experiments of mixed hydro-LCO were also performed to further clarify the “relay reaction” above, showing the highest yield of LPG and gasoline over mixed catalyst. The results indicate that the Y-cat and ZSM-5-cat have a synergistic effect on the conversion of hydro-diesel and corresponding value-added product yield and selective coke yield.

Keywords: synergistic effect, hydro-diesel cracking, FCC, zeolite catalyst, ethylene and propylene

Procedia PDF Downloads 36

Authors: Mahmoud Abdulhamid, Rifan Hardian, Prashant Bhatt, Shuvo Datta, Adrian Ramirez, Jorge Gascon, Mohamed Eddaoudi, Gyorgy Szekely

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Polybenzimidazole (PBI) is a high-performance polymer that exhibits high thermal and chemical stability. However, it suffers from low porosity and low fractional free volume, which hinder its application as separation material. Herein, we demonstrate the molecular engineering of gas separation materials by manipulating a PBI backbone possessing kinked moieties. PBI was selected as it contains NH groups which increase the affinity towards CO₂, increase sorption capacity, and favors CO₂ over other gasses. We have designed and synthesized an intrinsically microporous polybenzimidazole (iPBI) featuring a spirobisindane structure. Introducing a kinked moiety in conjunction with crosslinking enhanced the polymer properties, markedly increasing the gas separation performance. In particular, the BET surface area of PBI increased 30-fold by replacing a flat benzene ring with a kinked structure. iPBI displayed a good CO₂ uptake of 1.4 mmol g⁻¹ at 1 bar and 3.6 mmol g⁻¹ at 10 bar. Gas sorption uptake and breakthrough experiments were conducted using mixtures of CO₂/CH₄ (50%/50%) and CO₂/N₂ (50%/50%), which revealed the high selectivity of CO₂ over both CH₄ and N₂. The obtained CO₂/N₂ selectivity is attractive for power plant flue gas application requiring CO₂ capturing materials. Energy and process simulations of biogas CO₂ removal demonstrated that up to 70% of the capture energy could be saved when iPBI was used rather than the current amine technology (methyl diethanolamine [MDEA]). Similarly, the combination of iPBI and MDEA in a hybrid system exhibited the highest CO₂ capture yield (99%), resulting in nearly 50% energy saving. The concept of enhancing the porosity of PBI using kinked moieties provides new scope for designing highly porous polybenzimidazoles for various separation processes.

Keywords: polybenzimidazole (PBI), intrinsically microporous polybenzimidazole (iPBI), gas separation, pnergy and process simulations

Procedia PDF Downloads 59

Authors: F. Lazzeri, I. Reiter

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Energy production optimization has been traditionally very important for utilities in order to improve resource consumption. However, load forecasting is a challenging task, as there are a large number of relevant variables that must be considered, and several strategies have been used to deal with this complex problem. This is especially true also in microgrids where many elements have to adjust their performance depending on the future generation and consumption conditions. The goal of this paper is to present a solution for short-term load forecasting in microgrids, based on three machine learning experiments developed in R and web services built and deployed with different components of Cortana Intelligence Suite: Azure Machine Learning, a fully managed cloud service that enables to easily build, deploy, and share predictive analytics solutions; SQL database, a Microsoft database service for app developers; and PowerBI, a suite of business analytics tools to analyze data and share insights. Our results show that Boosted Decision Tree and Fast Forest Quantile regression methods can be very useful to predict hourly short-term consumption in microgrids; moreover, we found that for these types of forecasting models, weather data (temperature, wind, humidity and dew point) can play a crucial role in improving the accuracy of the forecasting solution. Data cleaning and feature engineering methods performed in R and different types of machine learning algorithms (Boosted Decision Tree, Fast Forest Quantile and ARIMA) will be presented, and results and performance metrics discussed.

Keywords: time-series, features engineering methods for forecasting, energy demand forecasting, Azure Machine Learning

Procedia PDF Downloads 272

Authors: P. Karthick, K. Mahesh

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Video has become an increasingly significant component of our digital everyday contact. With the advancement of greater contents and shows of the resolution, its significant volume poses serious obstacles to the objective of receiving, distributing, compressing, and revealing video content of high quality. In this paper, we propose the primary beginning to complete a deep video compression model that jointly upgrades all video compression components. The video compression method involves splitting the video into frames, comparing the images using convolutional neural networks (CNN) to remove duplicates, repeating the single image instead of the duplicate images by recognizing and detecting minute changes using generative adversarial network (GAN) and recorded with long short-term memory (LSTM). Instead of the complete image, the small changes generated using GAN are substituted, which helps in frame level compression. Pixel wise comparison is performed using K-nearest neighbours (KNN) over the frame, clustered with K-means, and singular value decomposition (SVD) is applied for each and every frame in the video for all three color channels [Red, Green, Blue] to decrease the dimension of the utility matrix [R, G, B] by extracting its latent factors. Video frames are packed with parameters with the aid of a codec and converted to video format, and the results are compared with the original video. Repeated experiments on several videos with different sizes, duration, frames per second (FPS), and quality results demonstrate a significant resampling rate. On average, the result produced had approximately a 10% deviation in quality and more than 50% in size when compared with the original video.

Keywords: video compression, K-means clustering, convolutional neural network, generative adversarial network, singular value decomposition, pixel visualization, stochastic gradient descent, frame per second extraction, RGB channel extraction, self-detection and deciding system

Procedia PDF Downloads 161

Authors: Fazil Hasan, M. Shafiq Ansari, Mohammad Muslim

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Zygogramma bicolorata Pallister (Coleoptera: Chrysomelidae) is an exotic insect and effective biocontrol agent of Parthenium hysterophorus L. (Asteraceae). Our study aimed to determine the induction and termination of diapause, in response to abiotic (temperature and moisture) and biotic factors (age and reproductive status) and the effect of diapause on adult longevity and female fecundity. The adults burrowed into the soil about 1–6 cm below the surface for diapause at any time from July to December with a peak of 70% in the 2nd week of December at Aligarh region, India. The termination of diapause took place in May and June with the commencement of monsoon rains. Non-diapausing adults were also capable of breeding during winter under laboratory conditions. There was a significantly increased in the percentage of diapaused adults in subsequent generation i.e. 4% in F1 generation and 90% in F7 generation. The percentage of diapause was also significantly increased with age of adults. It has a positive effect on female fecundity as compared to the fecundity in pre-diapaused duration. Experiments proved that soil moisture played an important role in providing the conditions for initiation and termination of diapause. The adults which undergone diapause in January and February were continuously exposed to 35º, 40º and 45º C for one week and a daily dose of 10 and 8 hours for 6 and 5 days, respectively resulting in termination of diapause. This method may be used to initiate mass multiplication for carrying out releases early in the season. Exposure of adults to extremely low temperatures i.e. 5º and 10º C induced 94.3% and 92.5% diapause, respectively with no adult mortality. Therefore, low temperatures can also be used as a medium for the storage of mass reared beetles for a long time without having negative effect on their longevity and fecundity. Thus, our findings are of great utility in the biological suppression of P. hysterophorus as it will enhance the effectiveness of this beetle through manipulation of diapause.

Keywords: Zygogramma bicolorata, environmental factors, age, sex, diapause, Parthenium hysterophorus, biocontrol

Procedia PDF Downloads 279

Authors: J. DeBoard, R. Dietrich, J. Hughes, K. Yurko, G. Harms

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Alzheimer’s disease (AD) is a predominant type of dementia and is likely a major cause of neural network impairment. The pathogenesis of this neurodegenerative disorder has yet to be fully elucidated. There are currently no known cures for the disease, and the best hope is to be able to detect it early enough to impede its progress. Beyond age and genetics, another prevalent risk factor for AD might be traumatic brain injury (TBI), which has similar neurodegenerative hallmarks. Our research focuses on obtaining information and methods to be able to predict when neurodegenerative effects might occur at a clinical level by observation of events at a cellular and molecular level in model mice. First, we wish to introduce our evidence that brain damage can be observed via brain imaging prior to the noticeable loss of neuromuscular control in model mice of AD. We then show our evidence that some blood biomarkers might be able to be early predictors of AD in the same model mice. Thus, we were interested to see if we might be able to predict which mice might show long-term neurodegenerative effects due to differing degrees of TBI and what level of TBI causes further damage and earlier death to the AD model mice. Upon application of TBIs via an apparatus to effectively induce extremely mild to mild TBIs, wild-type (WT) mice and AD mouse models were tested for cognition, neuromuscular control, olfactory ability, blood biomarkers, and brain imaging. Experiments are currently still in process, and more results are therefore forthcoming. Preliminary data suggest that neuromotor control diminishes as well as olfactory function for both AD and WT mice after the administration of five consecutive mild TBIs. Also, seizure activity increases significantly for both AD and WT after the administration of the five TBI treatment. If future data supports these findings, important implications about the effect of TBI on those at risk for AD might be possible.

Keywords: Alzheimer's disease, blood biomarker, neurodegeneration, neuromuscular control, olfaction, traumatic brain injury

Procedia PDF Downloads 103

Authors: Gulyas Erzsebet

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The multimerisation of proteins is a common feature of many cellular processes; however, it could also impair protein functions and/or be associated with the occurrence of diseases. Thus, development of a research tool monitoring the appearance/presence of multimeric protein forms has great importance for a variety of research fields. Such a tool is potentially applicable in the ante-mortem diagnosis of certain conformational diseases, such as transmissible spongiform encephalopathies (TSE) and Alzheimer’s disease. These conditions are accompanied by the appearance of aggregated protein multimers, present in low concentrations in various tissues. This detection is particularly relevant for TSE where the handling of tissues derived from affected individuals and of meat products of infected animals have become an enormous health concern. Here we demonstrate the potential of such a multimer detection approach in TSE by developing a facile approach. The Biospiral-Detect system resembles a traditional sandwich ELISA, except that the capturing antibody that is attached to a solid surface and the detecting antibody is directed against the same or overlapping epitopes. As a consequence, the capturing antibody shields the epitope on the captured monomer from reacting with the detecting antibody, therefore monomers are not detected. Thus, MDS is capable of detecting only protein multimers with high specificity. We developed an alternative system as well, where RNA aptamers were employed instead of monoclonal antibodies. In order to minimize degradation, the 3' and 5' ends of the aptamer contained deoxyribonucleotides and phosphorothioate linkages. When compared the monoclonal antibodies-based system with the aptamers-based one, the former proved to be superior. Thus all subsequent experiments were conducted by employing the Biospiral -Detect modified sandwich ELISA kit. Our approach showed an order of magnitude higher sensitivity toward mulimers than monomers suggesting that this approach may become a valuable diagnostic tool for conformational diseases that are accompanied by multimerization.

Keywords: diagnosis, ELISA, Prion, TSE

Procedia PDF Downloads 225

Authors: Adamu S. Salawu, Ibrahim O. Isah

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Direct solution to several forms of fourth-order ordinary differential equations is not easily obtained without first reducing them to a system of first-order equations. Thus, numerical methods are being developed with the underlying techniques in the literature, which seeks to approximate some classes of fourth-order initial value problems with admissible error bounds. Multistep methods present a great advantage of the ease of implementation but with a setback of several functions evaluation for every stage of implementation. However, hybrid methods conventionally show a slightly higher order of truncation for any k-step linear multistep method, with the possibility of obtaining solutions at off mesh points within the interval of solution. In the light of the foregoing, we propose the continuous form of a hybrid multistep method with Chebyshev polynomial as a basis function for the numerical integration of fourth-order initial value problems of ordinary differential equations. The basis function is interpolated and collocated at some points on the interval [0, 2] to yield a system of equations, which is solved to obtain the unknowns of the approximating polynomial. The continuous form obtained, its first and second derivatives are evaluated at carefully chosen points to obtain the proposed block method needed to directly approximate fourth-order initial value problems. The method is analyzed for convergence. Implementation of the method is done by conducting numerical experiments on some test problems. The outcome of the implementation of the method suggests that the method performs well on problems with oscillatory or trigonometric terms since the approximations at several points on the solution domain did not deviate too far from the theoretical solutions. The method also shows better performance compared with an existing hybrid method when implemented on a larger interval of solution.

Keywords: Chebyshev polynomial, collocation, hybrid multistep method, initial value problems, interpolation

Procedia PDF Downloads 100