Search results for: bloom filter

Authors: Lina Wu

Abstract:

The excessive discharge of nitrogen in sewage greatly intensifies the eutrophication of water bodies and poses a threat to water quality. Nitrogen pollution control has become a global concern. Currently, the problem of water pollution in China is still not optimistic. As a typical high ammonia nitrogen organic wastewater, landfill leachate is more difficult to treat than domestic sewage because of its complex water quality, high toxicity, and high concentration.Many studies have shown that the autotrophic anammox bacteria in nature can combine nitrous and ammonia nitrogen without carbon source through functional genes to achieve total nitrogen removal, which is very suitable for the removal of nitrogen from leachate. In addition, the process also saves a lot of aeration energy consumption than the traditional nitrogen removal process. Therefore, anammox plays an important role in nitrogen conversion and energy saving. The process composed of short-range nitrification and denitrification coupled an ammo ensures the removal of total nitrogen and improves the removal efficiency, meeting the needs of the society for an ecologically friendly and cost-effective nutrient removal treatment technology. Continuous flow process for treating late leachate [an up-flow anaerobic sludge blanket reactor (UASB), anoxic/oxic (A/O)–anaerobic ammonia oxidation reactor (ANAOR or anammox reactor)] has been developed to achieve autotrophic deep nitrogen removal. In this process, the optimal process parameters such as hydraulic retention time and nitrification flow rate have been obtained, and have been applied to the rapid start-up and stable operation of the process system and high removal efficiency. Besides, finding the characteristics of microbial community during the start-up of anammox process system and analyzing its microbial ecological mechanism provide a basis for the enrichment of anammox microbial community under high environmental stress. One research developed partial nitrification-Anammox (PN/A) using an internal circulation (IC) system and a biological aerated filter (BAF) biofilm reactor (IBBR), where the amount of water treated is closer to that of landfill leachate. However, new high-throughput sequencing technology is still required to be utilized to analyze the changes of microbial diversity of this system, related functional genera and functional genes under optimal conditions, providing theoretical and further practical basis for the engineering application of novel anammox system in biogas slurry treatment and resource utilization.

Keywords: nutrient removal and recovery, leachate, anammox, partial nitrification

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Authors: Jurriaan Gillissen

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This work is concerned with stabilizing the numerical integration of the Navier-Stokes equation (NSE), backwards in time. Applications involve the detection of sources of, e.g., sound, heat, and pollutants. Stable reverse numerical integration of parabolic differential equations is also relevant for image de-blurring. While the literature addresses the reverse integration problem of the advection-diffusion equation, the problem of numerical reverse integration of the NSE has, to our knowledge, not yet been addressed. Owing to the presence of viscosity, the NSE is irreversible, i.e., when going backwards in time, the fluid behaves, as if it had a negative viscosity. As an effect, perturbations from the perfect solution, due to round off errors or discretization errors, grow exponentially in time, and reverse integration of the NSE is inherently unstable, regardless of using an implicit time integration scheme. Consequently, some sort of filtering is required, in order to achieve a stable, numerical, reversed integration. The challenge is to find a filter with a minimal adverse affect on the accuracy of the reversed integration. In the present work, we explore an adjoint gradient method (AGM) to achieve this goal, and we apply this technique to two-dimensional (2D), decaying turbulence. The AGM solves for the initial velocity field u0 at t = 0, that, when integrated forward in time, produces a final velocity field u1 at t = 1, that is as close as is feasibly possible to some specified target field v1. The initial field u0 defines a minimum of a cost-functional J, that measures the distance between u1 and v1. In the minimization procedure, the u0 is updated iteratively along the gradient of J w.r.t. u0, where the gradient is obtained by transporting J backwards in time from t = 1 to t = 0, using the adjoint NSE. The AGM thus effectively replaces the backward integration by multiple forward and backward adjoint integrations. Since the viscosity is negative in the adjoint NSE, each step of the AGM is numerically stable. Nevertheless, when applied to turbulence, the AGM develops instabilities, which limit the backward integration to small times. This is due to the exponential divergence of phase space trajectories in turbulent flow, which produces a multitude of local minima in J, when the integration time is large. As an effect, the AGM may select unphysical, noisy initial conditions. In order to improve this situation, we propose two remedies. First, we replace the integration by a sequence of smaller integrations, i.e., we divide the integration time into segments, where in each segment the target field v1 is taken as the initial field u0 from the previous segment. Second, we add an additional term (regularizer) to J, which is proportional to a high-order Laplacian of u0, and which dampens the gradients of u0. We show that suitable values for the segment size and for the regularizer, allow a stable reverse integration of 2D decaying turbulence, with accurate results for more then O(10) turbulent, integral time scales.

Keywords: time reversed integration, parabolic differential equations, adjoint gradient method, two dimensional turbulence

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Authors: Minghui Zhang, Sirine Fkaier, Sabri Fernana, Svetlana Kiseleva, Denis Kiselev

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The real-time identification of bacteria and fungi is difficult because they emit much weaker signals than pollen. In 2020, Plair developed Rapid-E+, which extends abilities of Rapid-E to detect smaller bioaerosols such as bacteria and fungal spores with diameters down to 0.3 µm, while keeping the similar or even better capability for measurements of large bioaerosols like pollen. Rapid-E+ enables simultaneous measurements of (1) time-resolved, polarization and angle dependent Mie scattering patterns, (2) fluorescence spectra resolved in 16 channels, and (3) fluorescence lifetime of individual particles. Moreover, (4) it provides 2D Mie scattering images which give the full information on particle morphology. The parameters of every single bioaerosol aspired into the instrument are subsequently analysed by machine learning. Firstly, pure species of microbes, e.g., Bacillus subtilis (a species of bacteria), and Penicillium chrysogenum (a species of fungal spores), were aerosolized in a bioaerosol chamber for Rapid-E+ training. Afterwards, we tested microbes under different concentrations. We used several steps of data analysis to classify and identify microbes. All single particles were analysed by the parameters of light scattering and fluorescence in the following steps. (1) They were treated with a smart filter block to get rid of non-microbes. (2) By classification algorithm, we verified the filtered particles were microbes based on the calibration data. (3) The probability threshold (defined by the user) step provides the probability of being microbes ranging from 0 to 100%. We demonstrate how Rapid-E+ identified simultaneously microbes based on the results of Bacillus subtilis (bacteria) and Penicillium chrysogenum (fungal spores). By using machine learning, Rapid-E+ achieved identification precision of 99% against the background. The further classification suggests the precision of 87% and 89% for Bacillus subtilis and Penicillium chrysogenum, respectively. The developed algorithm was subsequently used to evaluate the performance of microbe classification and quantification in real-time. The bacteria and fungi were aerosolized again in the chamber with different concentrations. Rapid-E+ can classify different types of microbes and then quantify them in real-time. Rapid-E+ enables classifying different types of microbes and quantifying them in real-time. Rapid-E+ can identify pollen down to species with similar or even better performance than the previous version (Rapid-E). Therefore, Rapid-E+ is an all-in-one instrument which classifies and quantifies not only pollen, but also bacteria and fungi. Based on the machine learning platform, the user can further develop proprietary algorithms for specific microbes (e.g., virus aerosols) and other aerosols (e.g., combustion-related particles that contain polycyclic aromatic hydrocarbons).

Keywords: bioaerosols, laser-induced fluorescence, Mie-scattering, microorganisms

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Authors: Veronica Caprai, Katrin Schollbach, Miruna V. A. Florea, H. J. H. Brouwers

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Nowadays MSWI (Municipal Solid Waste Incineration) bottom ash (BA) produced by Waste-to-Energy (WtE) plants represents the majority of the solid residues derived from MSW incineration. Once processed, the BA is often landfilled resulting in possible environmental problems, additional costs for the plant and increasing occupation of public land. In order to limit this phenomenon, European countries such as the Netherlands aid the utilization of MSWI BA in the construction field, by providing standards about the leaching of contaminants into the environment (Dutch Soil Quality Decree). Commonly, BA has a particle size below 32 mm and a heterogeneous chemical composition, depending on its source. By washing coarser BA, an MSWI sludge is obtained. It is characterized by a high content of heavy metals, chlorides, and sulfates as well as a reduced particle size (below 0.25 mm). To lower its environmental impact, MSWI sludge is filtered or centrifuged for removing easily soluble contaminants, such as chlorides. However, the presence of heavy metals is not easily reduced, compromising its possible application. For lowering the leaching of those contaminants, the use of MSWI residues in combination with cement represents a precious option, due to the known retention of those ions into the hydrated cement matrix. Among the applications, the European standard for common cement EN 197-1:1992 allows the incorporation of up to 5% by mass of a minor additional constituent (MAC), such as fly ash or blast furnace slag but also an unspecified filler into cement. To the best of the author's knowledge, although it is widely available, it has the appropriate particle size and a chemical composition similar to cement, FC has not been investigated as possible MAC in cement production. Therefore, this paper will address the suitability of MSWI FC as MAC for CEM I 52.5 R, within a 5% maximum replacement by mass. After physical and chemical characterization of the raw materials, the crystal phases of the pastes are determined by XRD for 3 replacement levels (1%, 3%, and 5%) at different ages. Thereafter, the impact of FC on mechanical and environmental performances of cement is assessed according to EN 196-1 and the Dutch Soil Quality Decree, respectively. The investigation of the reaction products evidences the formation of layered double hydroxides (LDH), in the early stage of the reaction. Mechanically the presence of FC results in a reduction of 28 days compressive strength by 8% for a replacement of 5% wt., compared with the pure CEM I 52.5 R without any MAC. In contrast, the flexural strength is not affected by the presence of FC. Environmentally, the Dutch legislation for the leaching of contaminants for unshaped (granular) material is satisfied. Based on the collected results, FC represents a suitable candidate as MAC in cement production.

Keywords: environmental impact evaluation, Minor additional constituent, MSWI residues, X-ray diffraction crystallography

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Authors: Atchara Sankom, Warapa Mahakarnchanakul, Ronnarit Rittiron, Tanaboon Sajjaanantakul, Thammasak Thongket

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Vegetables are frequently contaminated with pesticides residues resulting in the most food safety concern among agricultural products. The objective of this work was to develop a method to detect the organophosphate (OP) pesticides residues in vegetables using Near Infrared (NIR) spectroscopy technique. Low concentration (ppm) of OP pesticides in vegetables were investigated. The experiment was divided into 2 sections. In the first section, Chinese kale spiked with different concentrations of chlorpyrifos pesticide residues (0.5-100 ppm) was chosen as the sample model to demonstrate the appropriate conditions of sample preparation, both for a solution or solid sample. The spiked samples were extracted with acetone. The sample extracts were applied as solution samples, while the solid samples were prepared by the dry-extract system for infrared (DESIR) technique. The DESIR technique was performed by embedding the solution sample on filter paper (GF/A) and then drying. The NIR spectra were measured with the transflectance mode over wavenumber regions of 12,500-4000 cm⁻¹. The QuEChERS method followed by gas chromatography-mass spectrometry (GC-MS) was performed as the standard method. The results from the first section showed that the DESIR technique with NIR spectroscopy demonstrated good accurate calibration result with R² of 0.93 and RMSEP of 8.23 ppm. However, in the case of solution samples, the prediction regarding the NIR-PLSR (partial least squares regression) equation showed poor performance (R² = 0.16 and RMSEP = 23.70 ppm). In the second section, the DESIR technique coupled with NIR spectroscopy was applied to the detection of OP pesticides in vegetables. Vegetables (Chinese kale, cabbage and hot chili) were spiked with OP pesticides (chlorpyrifos ethion and profenofos) at different concentrations ranging from 0.5 to 100 ppm. Solid samples were prepared (based on the DESIR technique), then samples were scanned by NIR spectrophotometer at ambient temperature (25+2°C). The NIR spectra were measured as in the first section. The NIR- PLSR showed the best calibration equation for detecting low concentrations of chlorpyrifos residues in vegetables (Chinese kale, cabbage and hot chili) according to the prediction set of R2 and RMSEP of 0.85-0.93 and 8.23-11.20 ppm, respectively. For ethion residues, the best calibration equation of NIR-PLSR showed good indexes of R² and RMSEP of 0.88-0.94 and 7.68-11.20 ppm, respectively. As well as the results for profenofos pesticide, the NIR-PLSR also showed the best calibration equation for detecting the profenofos residues in vegetables according to the good index of R² and RMSEP of 0.88-0.97 and 5.25-11.00 ppm, respectively. Moreover, the calibration equation developed in this work could rapidly predict the concentrations of OP pesticides residues (0.5-100 ppm) in vegetables, and there was no significant difference between NIR-predicted values and actual values (data from GC-MS) at a confidence interval of 95%. In this work, the proposed method using NIR spectroscopy involving the DESIR technique has proved to be an efficient method for the screening detection of OP pesticides residues at low concentrations, and thus increases the food safety potential of vegetables for domestic and export markets.

Keywords: NIR spectroscopy, organophosphate pesticide, vegetable, food safety

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Authors: R. Simide, T. Miard

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Integrated multi-trophic aquaculture (IMTA) is used to reduce waste from aquaculture and increase productivity by co-cultured species. In this study, we designed a recirculating multi-trophic aquaculture system which requires low energy consumption, low water renewal and easy-care. European seabass (Dicentrarchus labrax) were raised with co-cultured sea urchin (Paracentrotus lividus), deteritivorous polychaete fed on settled particulate matter, mussels (Mytilus galloprovincialis) used to extract suspended matters, macroalgae (Ulva sp.) used to uptake dissolved nutrients and gastropod (Phorcus turbinatus) used to clean the series of 4 tanks from fouling. Experiment was performed in triplicate during one month in autumn under an experimental greenhouse at the Institute Océanographique Paul Ricard (IOPR). Thanks to the absence of a physical filter, any pomp was needed to pressure water and the water flow was carried out by a single air-lift followed by gravity flow.Total suspended solids (TSS), biochemical oxygen demand (BOD5), turbidity, phytoplankton estimation and dissolved nutrients (ammonium NH₄, nitrite NO₂⁻, nitrate NO₃⁻ and phosphorus PO₄³⁻) were measured weekly while dissolved oxygen and pH were continuously recorded. Dissolved nutrients stay under the detectable threshold during the experiment. BOD5 decreased between fish and macroalgae tanks. TSS highly increased after 2 weeks and then decreased at the end of the experiment. Those results show that bioremediation can be well used for aquaculture system to keep optimum growing conditions. Fish were the only feeding species by an external product (commercial fish pellet) in the system. The others species (extractive species) were fed from waste streams from the tank above or from Ulva produced by the system for the sea urchin. In this way, between the fish aquaculture only and the addition of the extractive species, the biomass productivity increase by 5.7. In other words, the food conversion ratio dropped from 1.08 with fish only to 0.189 including all species. This experimental recirculating multi-trophic aquaculture system was efficient enough to reduce waste and increase productivity. In a second time, this technology has been reproduced at a commercial scale. The IOPR in collaboration with Les 4 Marais company run for 6 month a recirculating IMTA in 8000 m² of water allocate between 4 marsh ponds. A similar air-lift and gravity recirculating system was design and only one feeding species of shrimp (Palaemon sp.) was growth for 3 extractive species. Thanks to this joint work at the laboratory and commercial scales we will be able to challenge IMTA system and discuss about this sustainable aquaculture technology.

Keywords: bioremediation, integrated multi-trophic aquaculture (IMTA), laboratory and commercial scales, recirculating aquaculture, sustainable

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Authors: Sharmeen Rahman, Daniel Schmidt, Jane Hughes

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Paratya australiensis Kemp (Decapoda: Atyidae) is a widely distributed indigenous freshwater shrimp, highly abundant in eastern Australia. This species has been considered as a model stream organism to study genetics, dispersal, biology, behaviour and evolution in Atyids. Paratya has a filter feeding and scavenging habit which plays a significant role in the formation of lotic community structure. It has been shown to reduce periphyton and sediment from hard substrates of coastal streams and hence acts as a strongly-interacting ecosystem macroconsumer. Besides, Paratya is one of the major food sources for stream dwelling fishes. Paratya australiensis is a cryptic species complex consisting of 9 highly divergent mitochondrial DNA lineages. Among them, one lineage has been observed to favour upstream sites at higher altitudes, with cooler water temperatures. This study aims to identify local adaptation in upstream and downstream populations of this lineage in three streams in the Conondale Range, North-eastern Brisbane, Queensland, Australia. Two populations (up and down stream) from each stream have been chosen to test for local adaptation, and a parallel pattern of adaptation is expected across all streams. Six populations each consisting of 24 individuals were sequenced using the Restriction Site Associated DNA-seq (RAD-seq) technique. Genetic markers (SNPs) were developed using double digest RAD sequencing (ddRAD-seq). These were used for de novo assembly of Paratya genome. De novo assembly was done using the STACKs program and produced 56, 344 loci for 47 individuals from one stream. Among these individuals, 39 individuals shared 5819 loci, and these markers are being used to test for local adaptation using Fst outlier tests (Arlequin) and Bayesian analysis (BayeScan) between up and downstream populations. Fst outlier test detected 27 loci likely to be under selection and the Bayesian analysis also detected 27 loci as under selection. Among these 27 loci, 3 loci showed evidence of selection at a significance level using BayeScan program. On the other hand, up and downstream populations are strongly diverged at neutral loci with a Fst =0.37. Similar analysis will be done with all six populations to determine if there is a parallel pattern of adaptation across all streams. Furthermore, multi-locus among population covariance analysis will be done to identify potential markers under selection as well as to compare single locus versus multi-locus approaches for detecting local adaptation. Adaptive genes identified in this study can be used for future studies to design primers and test for adaptation in related crustacean species.

Keywords: Paratya australiensis, rainforest streams, selection, single nucleotide polymorphism (SNPs)

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Authors: Ragaa T. Darwish, Maha A. Demellawy, Haidy M. Megahed, Doreen N. Younan, Wael S. Kholeif

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The testing of drug abuse is authentic in order to affirm the misuse of drugs. Several analytical approaches have been developed for the detection of drugs of abuse in pharmaceutical and common biological samples, but few methodologies have been created to identify them from fingerprints. Liquid Chromatography-Mass Spectrometry (LC-MS) plays a major role in this field. The current study aimed at assessing the possibility of detection of some drugs of abuse (tramadol, clonazepam, and phenobarbital) from fingerprints using LC-MS in drug abusers. The aim was extended in order to assess the possibility of detection of the above-mentioned drugs in fingerprints of drug handlers till three days of handling the drugs. The study was conducted on randomly selected adult individuals who were either drug abusers seeking treatment at centers of drug dependence in Alexandria, Egypt or normal volunteers who were asked to handle the different studied drugs (drug handlers). An informed consent was obtained from all individuals. Participants were classified into 3 groups; control group that consisted of 50 normal individuals (neither abusing nor handling drugs), drug abuser group that consisted of 30 individuals who abused tramadol, clonazepam or phenobarbital (10 individuals for each drug) and drug handler group that consisted of 50 individuals who were touching either the powder of drugs of abuse: tramadol, clonazepam or phenobarbital (10 individuals for each drug) or the powder of the control substances which were of similar appearance (white powder) and that might be used in the adulteration of drugs of abuse: acetyl salicylic acid and acetaminophen (10 individuals for each drug). Samples were taken from the handler individuals for three consecutive days for the same individual. The diagnosis of drug abusers was based on the current Diagnostic and Statistical Manual of Mental disorders (DSM-V) and urine screening tests using immunoassay technique. Preliminary drug screening tests of urine samples were also done for drug handlers and the control groups to indicate the presence or absence of the studied drugs of abuse. Fingerprints of all participants were then taken on a filter paper previously soaked with methanol to be analyzed by LC-MS using SCIEX Triple Quad or QTRAP 5500 System. The concentration of drugs in each sample was calculated using the regression equations between concentration in ng/ml and peak area of each reference standard. All fingerprint samples from drug abusers showed positive results with LC-MS for the tested drugs, while all samples from the control individuals showed negative results. A significant difference was noted between the concentration of the drugs and the duration of abuse. Tramadol, clonazepam, and phenobarbital were also successfully detected from fingerprints of drug handlers till 3 days of handling the drugs. The mean concentration of the chosen drugs of abuse among the handlers group decreased when the days of samples intake increased.

Keywords: drugs of abuse, fingerprints, liquid chromatography–mass spectrometry, tramadol

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Authors: Maritza Estela Garay-Rodriguez, Mirella Gutierrez-Arzaluz, Miguel Torres-Rodriguez, Violeta Mugica-Alvarez

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Arsenic is an element present in the earth's crust and is dispersed in the environment through natural processes and some anthropogenic activities. Naturally released into the environment through the weathering and erosion of sulphides mineral, some activities such as mining, the use of pesticides or wood preservatives potentially increase the concentration of arsenic in air, water, and soil. The natural arsenic release of a geological material is a threat to the world's drinking water sources. In aqueous phase is found in inorganic form, as arsenate and arsenite mainly, the contamination of groundwater by salts of this element originates what is known as endemic regional hydroarsenicism. The International Agency for Research on Cancer (IARC) categorizes the inorganic As within group I, as a substance with proven carcinogenic action for humans. It has been found the presence of As in groundwater in several countries such as Argentina, Mexico, Bangladesh, Canada and the United States. Regarding the concentration of arsenic in drinking water according to the World Health Organization (WHO) and the Environmental Protection Agency (EPA) establish maximum concentrations of 10 μg L⁻¹. In Mexico, in some states as Hidalgo, Morelos and Michoacán concentrations of arsenic have been found in bodies of water around 1000 μg L⁻¹, a concentration that is well above what is allowed by Mexican regulations with the NOM-127- SSA1-1994 that establishes a limit of 25 μg L⁻¹. Given this problem in Mexico, this research proposes the use of a natural Mexican zeolite (clinoptilolite type) native to the district of Etla in the central valley region of Oaxaca, as an adsorbent for the removal of arsenic. The zeolite was subjected to a conditioning with iron oxide by the precipitation-impregnation method with 0.5 M iron nitrate solution, in order to increase the natural adsorption capacity of this material. The removal of arsenic was carried out in a column with a fixed bed of conditioned zeolite, since it combines the advantages of a conventional filter with those of a natural adsorbent medium, providing a continuous treatment, of low cost and relatively easy to operate, for its implementation in marginalized areas. The zeolite was characterized by XRD, SEM/EDS, and FTIR before and after the arsenic adsorption tests, the results showed that the modification methods used are adequate to prepare adsorbent materials since it does not modify its structure, the results showed that with a particle size of 1.18 mm, an initial concentration of As (V) ions of 1 ppm, a pH of 7 and at room temperature, a removal of 98.7% was obtained with an adsorption capacity of 260 μg As g⁻¹ zeolite. The results obtained indicated that the conditioned zeolite is favorable for the elimination of arsenate in water containing up to 1000 μg As L⁻¹ and could be suitable for removing arsenate from pits of water.

Keywords: adsorption, arsenic, iron conditioning, natural zeolite

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Authors: Ning Chang, Zelong Yuan, Yunpeng Wang, Jianchun Wang

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Large eddy simulation (LES) has been extensively used in the investigation of turbulence. LES calculates the grid-resolved large-scale motions and leaves small scales modeled by sublfilterscale (SFS) models. Among the existing SFS models, the deconvolution model has been used successfully in the LES of the engineering flows and geophysical flows. Despite the wide application of deconvolution models, the effects of subfilter scale dynamics and filter anisotropy on the accuracy of SFS modeling have not been investigated in depth. The results of LES are highly sensitive to the selection of filters and the anisotropy of the grid, which has been overlooked in previous research. In the current study, two critical aspects of LES are investigated. Firstly, we analyze the influence of sub-filter scale (SFS) dynamics on the accuracy of direct deconvolution models (DDM) at varying filter-to-grid ratios (FGR) in isotropic turbulence. An array of invertible filters are employed, encompassing Gaussian, Helmholtz I and II, Butterworth, Chebyshev I and II, Cauchy, Pao, and rapidly decaying filters. The significance of FGR becomes evident, as it acts as a pivotal factor in error control for precise SFS stress prediction. When FGR is set to 1, the DDM models cannot accurately reconstruct the SFS stress due to the insufficient resolution of SFS dynamics. Notably, prediction capabilities are enhanced at an FGR of 2, resulting in accurate SFS stress reconstruction, except for cases involving Helmholtz I and II filters. A remarkable precision close to 100% is achieved at an FGR of 4 for all DDM models. Additionally, the further exploration extends to the filter anisotropy to address its impact on the SFS dynamics and LES accuracy. By employing dynamic Smagorinsky model (DSM), dynamic mixed model (DMM), and direct deconvolution model (DDM) with the anisotropic filter, aspect ratios (AR) ranging from 1 to 16 in LES filters are evaluated. The findings highlight the DDM's proficiency in accurately predicting SFS stresses under highly anisotropic filtering conditions. High correlation coefficients exceeding 90% are observed in the a priori study for the DDM's reconstructed SFS stresses, surpassing those of the DSM and DMM models. However, these correlations tend to decrease as lter anisotropy increases. In the a posteriori studies, the DDM model consistently outperforms the DSM and DMM models across various turbulence statistics, encompassing velocity spectra, probability density functions related to vorticity, SFS energy flux, velocity increments, strain-rate tensors, and SFS stress. It is observed that as filter anisotropy intensify, the results of DSM and DMM become worse, while the DDM continues to deliver satisfactory results across all filter-anisotropy scenarios. The findings emphasize the DDM framework's potential as a valuable tool for advancing the development of sophisticated SFS models for LES of turbulence.

Keywords: deconvolution model, large eddy simulation, subfilter scale modeling, turbulence

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Authors: Patrícia T. Souza, Marina Ansolin, Eduardo A. C. Batista, Antonio J. A. Meirelles, Matthieu Tubino

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Lipid oxidation is a major cause of the deterioration of the quality of the biodiesel, because the waste generated damages the engines. Among the main undesirable effects are the increase of viscosity and acidity, leading to the formation of insoluble gums and sediments which cause the blockage of fuel filters. The auto-oxidation is defined as the spontaneous reaction of atmospheric oxygen with lipids. Unsaturated fatty acids are usually the components affected by such reactions. They are present as free fatty acids, fatty esters and glycerides. To determine the oxidative stability of biodiesels, through the induction period, IP, the Rancimat method is used, which allows continuous monitoring of the induced oxidation process of the samples. During the oxidation of the lipids, volatile organic acids are produced as byproducts, in addition, other byproducts, including alcohols and carbonyl compounds, may be further oxidized to carboxylic acids. By the methodology developed in this work using ion chromatography, IC, analyzing the water contained in the conductimetric vessel, were quantified organic anions of carboxylic acids in samples subjected to oxidation induced by Rancimat. The optimized chromatographic conditions were: eluent water:acetone (80:20 v/v) with 0.5 mM sulfuric acid; flow rate 0.4 mL min-1; injection volume 20 µL; eluent suppressor 20 mM LiCl; analytical curve from 1 to 400 ppm. The samples studied were methyl biodiesel from soybean oil and unsaturated fatty acids standards: oleic, linoleic and linolenic. The induced oxidation kinetics curves were constructed by analyzing the water contained in the conductimetric vessels which were removed, each one, from the Rancimat apparatus at prefixed intervals of time. About 3 g of sample were used under the conditions of 110 °C and air flow rate of 10 L h-1. The water of each conductimetric Rancimat measuring vessel, where the volatile compounds were collected, was filtered through a 0.45 µm filter and analyzed by IC. Through the kinetic data of the formation of the organic anions of carboxylic acids, the formation rates of the same were calculated. The observed order of the rates of formation of the anions was: formate >>> acetate > hexanoate > valerate for the oleic acid; formate > hexanoate > acetate > valerate for the linoleic acid; formate >>> valerate > acetate > propionate > butyrate for the linolenic acid. It is possible to suppose that propionate and butyrate are obtained mainly from linolenic acid and that hexanoate is originated from oleic and linoleic acid. For the methyl biodiesel the order of formation of anions was: formate >>> acetate > valerate > hexanoate > propionate. According to the total rate of formation these anions produced during the induced degradation of the fatty acids can be assigned the order of reactivity: linolenic acid > linoleic acid >>> oleic acid.

Keywords: anions of carboxylic acids, biodiesel, ion chromatography, oxidation

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Authors: S. Ebadzadsahraei, H. Kazemian

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The main objective of this research was to measure particulate matter (PM₂.₅) and Volatile Organic Compound (VOCs) as two classes of air pollutants, at Prince George (PG) neighborhood in warm and cold seasons. To fulfill this objective, analytical protocols were developed for accurate sampling and measurement of the targeted air pollutants. PM₂.₅ samples were analyzed for their chemical composition (i.e., toxic trace elements) in order to assess their potential source of emission. The City of Prince George, widely known as the capital of northern British Columbia (BC), Canada, has been dealing with air pollution challenges for a long time. The city has several local industries including pulp mills, a refinery, and a couple of asphalt plants that are the primary contributors of industrial VOCs. In this research project, which is the first study of this kind in this region it measures physical and chemical properties of particulate air pollutants (PM₂.₅) at the city neighborhood. Furthermore, this study quantifies the percentage of VOCs at the city air samples. One of the outcomes of this project is updated data about PM₂.₅ and VOCs inventory in the selected neighborhoods. For examining PM₂.₅ chemical composition, an elemental analysis methodology was developed to measure major trace elements including but not limited to mercury and lead. The toxicity of inhaled particulates depends on both their physical and chemical properties; thus, an understanding of aerosol properties is essential for the evaluation of such hazards, and the treatment of such respiratory and other related diseases. Mixed cellulose ester (MCE) filters were selected for this research as a suitable filter for PM₂.₅ air sampling. Chemical analyses were conducted using Inductively Coupled Plasma Mass Spectrometry (ICP-MS) for elemental analysis. VOCs measurement of the air samples was performed using a Gas Chromatography-Flame Ionization Detector (GC-FID) and Gas Chromatography-Mass Spectrometry (GC-MS) allowing for quantitative measurement of VOC molecules in sub-ppb levels. In this study, sorbent tube (Anasorb CSC, Coconut Charcoal), 6 x 70-mm size, 2 sections, 50/100 mg sorbent, 20/40 mesh was used for VOCs air sampling followed by using solvent extraction and solid-phase micro extraction (SPME) techniques to prepare samples for measuring by a GC-MS/FID instrument. Air sampling for both PM₂.₅ and VOC were conducted in summer and winter seasons for comparison. Average concentrations of PM₂.₅ are very different between wildfire and daily samples. At wildfire time average of concentration is 83.0 μg/m³ and daily samples are 23.7 μg/m³. Also, higher concentrations of iron, nickel and manganese found at all samples and mercury element is found in some samples. It is able to stay too high doses negative effects.

Keywords: air pollutants, chemical analysis, particulate matter (PM₂.₅), volatile organic compound, VOCs

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Authors: Z. Karahaliloğlu, C. Hacker, M. Demirbilek, G. Seide, E. B. Denkbaş, T. Gries

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Currently, textile industry has played an important role in world’s economy, especially in developing countries. Dyes and pigments used in textile industry are significant pollutants. Most of theirs are azo dyes that have chromophore (-N=N-) in their structure. There are many methods for removal of the dyes from wastewater such as chemical coagulation, flocculation, precipitation and ozonation. But these methods have numerous disadvantages and alternative methods are needed for wastewater decolorization. Titanium-mediated photodegradation has been used generally due to non-toxic, insoluble, inexpensive, and highly reactive properties of titanium dioxide semiconductor (TiO2). Melt electrospinning is an attractive manufacturing process for thin fiber production through electrospinning from PP (Polyprophylene). PP fibers have been widely used in the filtration due to theirs unique properties such as hydrophobicity, good mechanical strength, chemical resistance and low-cost production. In this study, we aimed to investigate the effect of titanium nanoparticle localization and amine modification on the dye degradation. The applicability of the prepared chemical activated composite and pristine fabrics for a novel treatment of dyeing wastewater were evaluated.In this study, a photocatalyzer material was prepared from nTi (titanium dioxide nanoparticles) and PP by a melt-electrospinning technique. The electrospinning parameters of pristine PP and PP/nTi nanocomposite fabrics were optimized. Before functionalization with nTi, the surface of fabrics was activated by a technique using glutaraldehyde (GA) and polyethyleneimine to promote the dye degredation. Pristine PP and PP/nTi nanocomposite melt-electrospun fabrics were characterized using scanning electron microscopy (SEM) and X-Ray Photon Spectroscopy (XPS). Methyl orange (MO) was used as a model compound for the decolorization experiments. Photocatalytic performance of nTi-loaded pristine and nanocomposite melt-electrospun filters was investigated by varying initial dye concentration 10, 20, 40 mg/L). nTi-PP composite fabrics were successfully processed into a uniform, fibrous network of beadless fibers with diameters of 800±0.4 nm. The process parameters were determined as a voltage of 30 kV, a working distance of 5 cm, a temperature of the thermocouple and hotcoil of 260–300 ºC and a flow rate of 0.07 mL/h. SEM results indicated that TiO2 nanoparticles were deposited uniformly on the nanofibers and XPS results confirmed the presence of titanium nanoparticles and generation of amine groups after modification. According to photocatalytic decolarization test results, nTi-loaded GA-treated pristine or nTi-PP nanocomposite fabric filtern have superior properties, especially over 90% decolorization efficiency at GA-treated pristine and nTi-PP composite PP fabrics. In this work, as a photocatalyzer for wastewater treatment, surface functionalized with nTi melt-electrospun fabrics from PP were prepared. Results showed melt-electrospun nTi-loaded GA-tretaed composite or pristine PP fabrics have a great potential for use as a photocatalytic filter to decolorization of wastewater and thus, requires further investigation.

Keywords: titanium oxide nanoparticles, polyprophylene, melt-electrospinning

Procedia PDF Downloads 267

Authors: Sergio A. Navarro Tuch, Martin Rogelio Bustamante Bello, Leopoldo Julian Lechuga Lopez

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In recent years, Mexico’s population has seen a rise of different physiological and mental negative states. Two main consequences of this problematic are deficient work performance and high levels of stress generating and important impact on a person’s physical, mental and emotional health. Several approaches, such as the use of audiovisual stimulus to induce emotions and modify a person’s emotional state, can be applied in an effort to decreases these negative effects. With the use of different non-invasive physiological sensors such as EEG, luminosity and face recognition we gather information of the subject’s current emotional state. In a controlled environment, a subject is shown a series of selected images from the International Affective Picture System (IAPS) in order to induce a specific set of emotions and obtain information from the sensors. The raw data obtained is statistically analyzed in order to filter only the specific groups of information that relate to a subject’s emotions and current values of the physical variables in the controlled environment such as, luminosity, RGB light color, temperature, oxygen level and noise. Finally, a neural network based control algorithm is given the data obtained in order to feedback the system and automate the modification of the environment variables and audiovisual content shown in an effort that these changes can positively alter the subject’s emotional state. During the research, it was found that the light color was directly related to the type of impact generated by the audiovisual content on the subject’s emotional state. Red illumination increased the impact of violent images and green illumination along with relaxing images decreased the subject’s levels of anxiety. Specific differences between men and women were found as to which type of images generated a greater impact in either gender. The population sample was mainly constituted by college students whose data analysis showed a decreased sensibility to violence towards humans. Despite the early stage of the control algorithm, the results obtained from the population sample give us a better insight into the possibilities of emotional domotics and the applications that can be created towards the improvement of performance in people’s lives. The objective of this research is to create a positive impact with the application of technology to everyday activities; nonetheless, an ethical problem arises since this can also be applied to control a person’s emotions and shift their decision making.

Keywords: data analysis, emotional domotics, performance improvement, neural network

Procedia PDF Downloads 140

Authors: Oluwafunmibi Omotayo Fasanya, Augustine Kena Adjei

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Background and Aims: This meta-analysis aimed to evaluate the effect of vitamin D supplementation on key metabolic and cardiovascular parameters, such as glycated hemoglobin (HbA1C), fasting blood sugar (FBS), low-density lipoprotein (LDL), high-density lipoprotein (HDL), systolic blood pressure (SBP), and total vitamin D levels in patients with Type 2 diabetes mellitus (T2DM). Methods: A systematic search was performed across databases, including PubMed, Scopus, Embase, Web of Science, Cochrane Library, and ClinicalTrials.gov, from January 1990 to January 2024. A total of 4,177 relevant studies were initially identified. Using an unsupervised K-means clustering algorithm, publications were grouped based on common text features. Maximum entropy classification was then applied to filter studies that matched a pre-identified training set of 139 potentially relevant articles. These selected studies were manually screened for relevance. A parallel manual selection of all initially searched studies was conducted for validation. The final inclusion of studies was based on full-text evaluation, quality assessment, and meta-regression models using random effects. Sensitivity analysis and publication bias assessments were also performed to ensure robustness. Results: The unsupervised K-means clustering algorithm grouped the patients based on their responses to vitamin D supplementation, using key biomarkers such as HbA1C, FBS, LDL, HDL, SBP, and total vitamin D levels. Two primary clusters emerged: one representing patients who experienced significant improvements in these markers and another showing minimal or no change. Patients in the cluster associated with significant improvement exhibited lower HbA1C, FBS, and LDL levels after vitamin D supplementation, while HDL and total vitamin D levels increased. The analysis showed that vitamin D supplementation was particularly effective in reducing HbA1C, FBS, and LDL within this cluster. Furthermore, BMI, weight gain, and disease duration were identified as factors that influenced cluster assignment, with patients having lower BMI and shorter disease duration being more likely to belong to the improvement cluster. Conclusion: The findings of this machine learning-assisted meta-analysis confirm that vitamin D supplementation can significantly improve glycemic control and reduce the risk of cardiovascular complications in T2DM patients. The use of automated screening techniques streamlined the process, ensuring the comprehensive evaluation of a large body of evidence while maintaining the validity of traditional manual review processes.

Keywords: HbA1C, T2DM, SBP, FBS

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Authors: K. H. Reeta, Bhavana Prasher, Mitali Mukerji, Dhwani Dholakia, Sangeeta Khanna, Archana Vats, Shivam Pandey, Sandeep Seth, Subir Kumar Maulik

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Introduction Research has demonstrated a connection between coronary artery disease (CAD) and genetics. We did a deep literature mining using both bioinformatics and manual efforts to identify the susceptible polymorphisms in coronary artery disease. Further, the study sought to validate these findings in an Asian population. Methodology In first phase, we used an automated pipeline which organizes and presents structured information on SNPs, Population and Diseases. The information was obtained by applying Natural Language Processing (NLP) techniques to approximately 28 million PubMed abstracts. To accomplish this, we utilized Python scripts to extract and curate disease-related data, filter out false positives, and categorize them into 24 hierarchical groups using named Entity Recognition (NER) algorithms. From the extensive research conducted, a total of 466 unique PubMed Identifiers (PMIDs) and 694 Single Nucleotide Polymorphisms (SNPs) related to coronary artery disease (CAD) were identified. To refine the selection process, a thorough manual examination of all the studies was carried out. Specifically, SNPs that demonstrated susceptibility to CAD and exhibited a positive Odds Ratio (OR) were selected, and a final pool of 324 SNPs was compiled. The next phase involved validating the identified SNPs in DNA samples of 96 CAD patients and 37 healthy controls from Indian population using Global Screening Array. ResultsThe results exhibited out of 324, only 108 SNPs were expressed, further 4 SNPs showed significant difference of minor allele frequency in cases and controls. These were rs187238 of IL-18 gene, rs731236 of VDR gene, rs11556218 of IL16 gene and rs5882 of CETP gene. Prior researches have reported association of these SNPs with various pathways like endothelial damage, susceptibility of vitamin D receptor (VDR) polymorphisms, and reduction of HDL-cholesterol levels, ultimately leading to the development of CAD. Among these, only rs731236 had been studied in Indian population and that too in diabetes and vitamin D deficiency. For the first time, these SNPs were reported to be associated with CAD in Indian population. Conclusion: This pool of 324 SNP s is a unique kind of resource that can help to uncover risk associations in CAD. Here, we validated in Indian population. Further, validation in different populations may offer valuable insights and contribute to the development of a screening tool and may help in enabling the implementation of primary prevention strategies targeted at the vulnerable population.

Keywords: coronary artery disease, single nucleotide polymorphism, susceptible SNP, bioinformatics

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Authors: Sachin B. Patil, Narendra M. Kanhe

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A typical cane molasses based distillery generates 15 L of waste water per liter of alcohol production. Distillery waste with COD of over 1,00,000 mg/l and BOD of over 30,000 mg/l ranks high amongst the pollutants produced by industries both in magnitude and strength. Treatment and safe disposal of this waste is a challenging task since long. The high strength of waste water renders aerobic treatment very expensive and physico-chemical processes have met with little success. Thermophilic anaerobic treatment of distillery waste may provide high degree of treatment and better recovery of biogas. It may prove more feasible in most part of tropical country like India, where temperature is suitable for thermophilic micro-organisms. Researchers have reviled that, at thermophilic conditions due to increased destruction rate of organic matter and pathogens, higher digestion rate can be achieved. Literature review reveals that the variety of anaerobic reactors including anaerobic lagoon, conventional digester, anaerobic filter, two staged fixed film reactors, sludge bed and granular bed reactors have been studied, but little attempts have been made to evaluate the usefulness of thermophilic anaerobic treatment for treating distillery waste. The present study has been carried out, to study feasibility of thermophilic anaerobic digestion to facilitate the design of full scale reactor. A pilot scale anaerobic fixed film fixed bed reactor (AFFFB) of capacity 25m3 was designed, fabricated, installed and commissioned for thermophilic (55-65°C) anaerobic digestion at a constant pH of 6.5-7.5, because these temperature and pH ranges are considered to be optimum for biogas recovery from distillery wastewater. In these conditions, working of the reactor was studied, for different hydraulic retention times (HRT) (0.25days to 12days) and variable organic loading rates (361.46 to 7.96 Kg COD/m3d). The parameters such as flow rate and temperature, various chemical parameters such as pH, chemical oxygen demands (COD), biogas quantity, and biogas composition were regularly monitored. It was observed that, with the increase in OLR, the biogas production was increased, but the specific biogas yield decreased. Similarly, with the increase in HRT, the biogas production got decrease, but the specific biogas yield was increased. This may also be due to the predominant activity of acid producers to methane producers at the higher substrate loading rates. From the present investigation, it can be concluded that for thermophilic conditions the highest COD removal percentage was obtained at an HRT of 08 days, thereafter it tends to decrease from 8 to 12 days HRT. There is a little difference between COD removal efficiency of 8 days HRT (74.03%) and 5 day HRT (78.06%), therefore it would not be feasible to increase the reactor size by 1.5 times for mere 4 percent more efficiency. Hence, 5 days HRT is considered to be optimum, at which the biogas yield was 98 m3/day and specific biogas yield was 0.385 CH4 m3/Kg CODr.

Keywords: spent wash, anaerobic digestion, biomass, biogas

Procedia PDF Downloads 265

Authors: K. O’Mara, T. Cresswell

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Nearly half of the world’s population live near the coast, and as a result, estuaries and coastal bays in populated or industrialized areas often receive metal pollution. Heavy metals have a chemical affinity for sediment particles and can be stored in estuarine sediments and become biologically available under changing conditions. Organisms inhabiting estuaries can be exposed to metals from a variety of sources including metals dissolved in water, bound to sediment or within contaminated prey. Metal uptake and assimilation responses can vary even between species that are biologically similar, making pollution effects difficult to predict. A multi-trophic level experiment representing a common Eastern Australian estuarine food chain was used to study the sources for Cd, Mn and Zn uptake and assimilation in organisms occupying several trophic levels. Sand cockles (Katelysia scalarina), school prawns (Metapenaeus macleayi) and sand whiting (Sillago ciliata) were exposed to radiolabelled seawater, suspended sediment and food. Three pulse-chase trials on filter-feeding sand cockles were performed using radiolabelled phytoplankton (Tetraselmis sp.), benthic microalgae (Entomoneis sp.) and suspended sediment. Benthic microalgae had lower metal uptake than phytoplankton during labelling but higher cockle assimilation efficiencies (Cd = 51%, Mn = 42%, Zn = 63 %) than both phytoplankton (Cd = 21%, Mn = 32%, Zn = 33%) and suspended sediment (except Mn; (Cd = 38%, Mn = 42%, Zn = 53%)). Sand cockles were also sensitive to uptake of Cd, Mn and Zn dissolved in seawater. Uptake of these metals from the dissolved phase was negligible in prawns and fish, with prawns only accumulating metals during moulting, which were then lost with subsequent moulting in the depuration phase. Diet appears to be the main source of metal assimilation in school prawns, with 65%, 54% and 58% assimilation efficiencies from Cd, Mn and Zn respectively. Whiting fed contaminated prawns were able to exclude the majority of the metal activity through egestion, with only 10%, 23% and 11% assimilation efficiencies from Cd, Mn and Zn respectively. The findings of this study support previous studies that find diet to be the dominant accumulation source for higher level trophic organisms. These results show that assimilation efficiencies can vary depending on the source of exposure; sand cockles assimilated more Cd, Mn, and Zn from the benthic diatom than phytoplankton and assimilation was higher in sand whiting fed prawns compared to artificial pellets. The sensitivity of sand cockles to metal uptake and assimilation from a variety of sources poses concerns for metal availability to predators ingesting the clam tissue, including humans. The high tolerance of sand whiting to these metals is reflected in their widespread presence in Eastern Australian estuaries, including contaminated estuaries such as Botany Bay and Port Jackson.

Keywords: cadmium, food chain, metal, manganese, trophic, zinc

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Authors: Tobias Milz, L. Macpherson, Varvara Vetrova

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The law is a fundamental pillar of human societies as it shapes, controls and governs how humans conduct business, behave and interact with each other. Recent advances in computer-assisted technologies such as NLP, data science and AI are creating opportunities to support the practice, research and study of this pervasive domain. It is therefore not surprising that there has been an increase in investments into supporting technologies for the legal industry (also known as “legal tech” or “law tech”) over the last decade. A sub-discipline of particular appeal is concerned with assisted legal research. Supporting law researchers and practitioners to retrieve information from the vast amount of ever-growing legal documentation is of natural interest to the legal research community. One tool that has been in use for this purpose since the early nineteenth century is legal citation indexing. Among other use cases, they provided an effective means to discover new precedent cases. Nowadays, computer-assisted network analysis tools can allow for new and more efficient ways to reveal the “hidden” information that is conveyed through citation behavior. Unfortunately, access to openly available legal data is still lacking in New Zealand and access to such networks is only commercially available via providers such as LexisNexis. Consequently, there is a need to create, analyze and provide a legal citation network with sufficient data to support legal research tasks. This paper describes the development and analysis of a legal citation Network for New Zealand containing over 300.000 decisions from 125 different courts of all areas of law and jurisdiction. Using python, the authors assembled web crawlers, scrapers and an OCR pipeline to collect and convert court decisions from openly available sources such as NZLII into uniform and machine-readable text. This facilitated the use of regular expressions to identify references to other court decisions from within the decision text. The data was then imported into a graph-based database (Neo4j) with the courts and their respective cases represented as nodes and the extracted citations as links. Furthermore, additional links between courts of connected cases were added to indicate an indirect citation between the courts. Neo4j, as a graph-based database, allows efficient querying and use of network algorithms such as PageRank to reveal the most influential/most cited courts and court decisions over time. This paper shows that the in-degree distribution of the New Zealand legal citation network resembles a power-law distribution, which indicates a possible scale-free behavior of the network. This is in line with findings of the respective citation networks of the U.S. Supreme Court, Austria and Germany. The authors of this paper provide the database as an openly available data source to support further legal research. The decision texts can be exported from the database to be used for NLP-related legal research, while the network can be used for in-depth analysis. For example, users of the database can specify the network algorithms and metrics to only include specific courts to filter the results to the area of law of interest.

Keywords: case citation network, citation analysis, network analysis, Neo4j

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Authors: Manel Hammami, Gabriele Grandi

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In recent years, multilevel inverters have become more attractive for single-phase photovoltaic (PV) systems, due to their known advantages over conventional H-bridge pulse width-modulated (PWM) inverters. They offer improved output waveforms, smaller filter size, lower total harmonic distortion (THD), higher output voltages and others. The most common multilevel converter topologies, presented in literature, are the neutral-point-clamped (NPC), flying capacitor (FC) and Cascaded H-Bridge (CHB) converters. In both NPC and FC configurations, the number of components drastically increases with the number of levels what leads to complexity of the control strategy, high volume, and cost. Whereas, increasing the number of levels in case of the cascaded H-bridge configuration is a flexible solution. However, it needs isolated power sources for each stage, and it can be applied to PV systems only in case of PV sub-fields. In order to improve the ratio between the number of output voltage levels and the number of components, several hybrids and asymmetric topologies of multilevel inverters have been proposed in the literature such as the FC asymmetric H-bridge (FCAH) and the NPC asymmetric H-bridge (NPCAH) topologies. Another asymmetric multilevel inverter configuration that could have interesting applications is the cascaded asymmetric H-bridge (CAH), which is based on a modular half-bridge (two switches and one capacitor, also called level doubling network, LDN) cascaded to a full H-bridge in order to double the output voltage level. This solution has the same number of switches as the above mentioned AH configurations (i.e., six), and just one capacitor (as the FCAH). CAH is becoming popular, due to its simple, modular and reliable structure, and it can be considered as a retrofit which can be added in series to an existing H-Bridge configuration in order to double the output voltage levels. In this paper, an original and effective method for the analysis of the DC-link voltage ripple is given for single-phase asymmetric H-bridge multilevel inverters based on level doubling network (LDN). Different possible configurations of the asymmetric H-Bridge multilevel inverters have been considered and the analysis of input voltage and current are analytically determined and numerically verified by Matlab/Simulink for the case of cascaded asymmetric H-bridge multilevel inverters. A comparison between FCAH and the CAH configurations is done on the basis of the analysis of the DC and voltage ripple for the DC source (i.e., the PV system). The peak-to-peak DC and voltage ripple amplitudes are analytically calculated over the fundamental period as a function of the modulation index. On the basis of the maximum peak-to-peak values of low frequency and switching ripple voltage components, the DC capacitors can be designed. Reference is made to unity output power factor, as in case of most of the grid-connected PV generation systems. Simulation results will be presented in the full paper in order to prove the effectiveness of the proposed developments in all the operating conditions.

Keywords: asymmetric inverters, dc-link voltage, level doubling network, single-phase multilevel inverter

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Authors: Shin Woo Kim, Eui Ju Lee

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The recent development of biofuel production technology facilitates the use of bioethanol and biodiesel on automobile. Bioethanol, especially, can be used as a fuel for gasoline vehicles because the addition of ethanol has been known to increase octane number and reduce soot emissions. However, the wide application of biofuel has been still limited because of lack of detailed combustion properties such as auto-ignition temperature and pollutant emissions such as NOx and soot, which has been concerned mainly on the vehicle fire safety and environmental safety. In this study, the combustion characteristics of gasoline/ethanol fuel were investigated both numerically and experimentally. For auto-ignition temperature and NOx emission, the numerical simulation was performed on the well-stirred reactor (WSR) to simulate the homogeneous gasoline engine and to clarify the effect of ethanol addition in the gasoline fuel. Also, the response surface method (RSM) was introduced as a design of experiment (DOE), which enables the various combustion properties to be predicted and optimized systematically with respect to three independent variables, i.e., ethanol mole fraction, equivalence ratio and residence time. The results of stoichiometric gasoline surrogate show that the auto-ignition temperature increases but NOx yields decrease with increasing ethanol mole fraction. This implies that the bioethanol added gasoline is an eco-friendly fuel on engine running condition. However, unburned hydrocarbon is increased dramatically with increasing ethanol content, which results from the incomplete combustion and hence needs to adjust combustion itself rather than an after-treatment system. RSM results analyzed with three independent variables predict the auto-ignition temperature accurately. However, NOx emission had a big difference between the calculated values and the predicted values using conventional RSM because NOx emission varies very steeply and hence the obtained second order polynomial cannot follow the rates. To relax the increasing rate of dependent variable, NOx emission is taken as common logarithms and worked again with RSM. NOx emission predicted through logarithm transformation is in a fairly good agreement with the experimental results. For more tangible understanding of gasoline/ethanol fuel on pollutant emissions, experimental measurements of combustion products were performed in gasoline/ethanol pool fires, which is widely used as a fire source of laboratory scale experiments. Three measurement methods were introduced to clarify the pollutant emissions, i.e., various gas concentrations including NOx, gravimetric soot filter sampling for elements analysis and pyrolysis, thermophoretic soot sampling with transmission electron microscopy (TEM). Soot yield by gravimetric sampling was decreased dramatically as ethanol was added, but NOx emission was almost comparable regardless of ethanol mole fraction. The morphology of the soot particle was investigated to address the degree of soot maturing. The incipient soot such as a liquid like PAHs was observed clearly on the soot of higher ethanol containing gasoline, and the soot might be matured under the undiluted gasoline fuel.

Keywords: gasoline/ethanol fuel, NOx, pool fire, soot, well-stirred reactor (WSR)

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Authors: Soyon Kim, Edward Kim

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In order to retrieve information from the massive stream of songs in the music industry, music search by title, lyrics, artist, mood, and genre has become more important. Despite the subjectivity and controversy over the definition of music genres across different nations and cultures, automatic genre classification systems that facilitate the process of music categorization have been developed. Manual genre selection by music producers is being provided as statistical data for designing automatic genre classification systems. In this paper, an automatic music genre classification system utilizing non-negative matrix factorization (NMF) is proposed. Short-term characteristics of the music signal can be captured based on the timbre features such as mel-frequency cepstral coefficient (MFCC), decorrelated filter bank (DFB), octave-based spectral contrast (OSC), and octave band sum (OBS). Long-term time-varying characteristics of the music signal can be summarized with (1) the statistical features such as mean, variance, minimum, and maximum of the timbre features and (2) the modulation spectrum features such as spectral flatness measure, spectral crest measure, spectral peak, spectral valley, and spectral contrast of the timbre features. Not only these conventional basic long-term feature vectors, but also NMF based feature vectors are proposed to be used together for genre classification. In the training stage, NMF basis vectors were extracted for each genre class. The NMF features were calculated in the log spectral magnitude domain (NMF-LSM) as well as in the basic feature vector domain (NMF-BFV). For NMF-LSM, an entire full band spectrum was used. However, for NMF-BFV, only low band spectrum was used since high frequency modulation spectrum of the basic feature vectors did not contain important information for genre classification. In the test stage, using the set of pre-trained NMF basis vectors, the genre classification system extracted the NMF weighting values of each genre as the NMF feature vectors. A support vector machine (SVM) was used as a classifier. The GTZAN multi-genre music database was used for training and testing. It is composed of 10 genres and 100 songs for each genre. To increase the reliability of the experiments, 10-fold cross validation was used. For a given input song, an extracted NMF-LSM feature vector was composed of 10 weighting values that corresponded to the classification probabilities for 10 genres. An NMF-BFV feature vector also had a dimensionality of 10. Combined with the basic long-term features such as statistical features and modulation spectrum features, the NMF features provided the increased accuracy with a slight increase in feature dimensionality. The conventional basic features by themselves yielded 84.0% accuracy, but the basic features with NMF-LSM and NMF-BFV provided 85.1% and 84.2% accuracy, respectively. The basic features required dimensionality of 460, but NMF-LSM and NMF-BFV required dimensionalities of 10 and 10, respectively. Combining the basic features, NMF-LSM and NMF-BFV together with the SVM with a radial basis function (RBF) kernel produced the significantly higher classification accuracy of 88.3% with a feature dimensionality of 480.

Keywords: mel-frequency cepstral coefficient (MFCC), music genre classification, non-negative matrix factorization (NMF), support vector machine (SVM)

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Authors: Tatiane Benvenuti, Fernando Hamerski, Alexandre Giacobbo, Andrea M. Bernardes, Marco A. S. Rodrigues

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Population growth in urban areas has caused damages to the environment, a consequence of the uncontrolled dumping of domestic and industrial wastewater. The capacity of some plants to purify domestic and agricultural wastewater has been demonstrated by several studies. Since natural wetlands have the ability to transform, retain and remove nutrients, constructed wetlands have been used for wastewater treatment. They are widely recognized as an economical, efficient and environmentally acceptable means of treating many different types of wastewater. T. domingensis Pers. species have shown a good performance and low deployment cost to extract, detoxify and sequester pollutants. Constructed Floating Wetlands (CFWs) consist of emergent vegetation established upon a buoyant structure, floating on surface waters. The upper parts of the vegetation grow and remain primarily above the water level, while the roots extend down in the water column, developing an extensive under water-level root system. Thus, the vegetation grows hydroponically, performing direct nutrient uptake from the water column. Biofilm is attached on the roots and rhizomes, and as physical and biochemical processes take place, the system functions as a natural filter. The aim of this study is to diagnose the application of macrophytes in artificial floating in the treatment of domestic sewage in south Brazil. The T. domingensis Pers. plants were placed in a flotation system (polymer structure), in full scale, in a sewage treatment plant. The sewage feed rate was 67.4 m³.d⁻¹ ± 8.0, and the hydraulic retention time was 11.5 d ± 1.3. This CFW treat the sewage generated by 600 inhabitants, which corresponds to 12% of the population served by this municipal treatment plant. During 12 months, samples were collected every two weeks, in order to evaluate parameters as chemical oxygen demand (COD), biochemical oxygen demand in 5 days (BOD5), total Kjeldahl nitrogen (TKN), total phosphorus, total solids, and metals. The average removal of organic matter was around 55% for both COD and BOD5. For nutrients, TKN was reduced in 45.9% what was similar to the total phosphorus removal, while for total solids the reduction was 33%. For metals, aluminum, copper, and cadmium, besides in low concentrations, presented the highest percentage reduction, 82.7, 74.4 and 68.8% respectively. Chromium, iron, and manganese removal achieved values around 40-55%. The use of T. domingensis Pers. in artificial floating for sewage treatment is an effective and innovative alternative in Brazilian sewage treatment systems. The evaluation of additional parameters in the treatment system may give useful information in order to improve the removal efficiency and increase the quality of the water bodies.

Keywords: constructed wetland, floating system, sewage treatment, Typha domingensis Pers.

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Authors: Mohammad Moezzibadi, Isabelle Charpentier, Adrien Wanko, Robert Mosé

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The calibration of hydrodynamic parameters for subsurface constructed wetlands (CWs) is a sensitive process since highly non-linear equations are involved in unsaturated flow modeling. CW systems are engineered systems designed to favour natural treatment processes involving wetland vegetation, soil, and their microbial flora. Their significant efficiency at reducing the ecological impact of urban runoff has been recently proved in the field. Numerical flow modeling in a vertical variably saturated CW is here carried out by implementing the Richards model by means of a mixed hybrid finite element method (MHFEM), particularly well adapted to the simulation of heterogeneous media, and the van Genuchten-Mualem parametrization. For validation purposes, MHFEM results were compared to those of HYDRUS (a software based on a finite element discretization). As van Genuchten-Mualem soil hydrodynamic parameters depend on water content, their estimation is subject to considerable experimental and numerical studies. In particular, the sensitivity analysis performed with respect to the van Genuchten-Mualem parameters reveals a predominant influence of the shape parameters α, n and the saturated conductivity of the filter on the piezometric heads, during saturation and desaturation. Modeling issues arise when the soil reaches oven-dry conditions. A particular attention should also be brought to boundary condition modeling (surface ponding or evaporation) to be able to tackle different sequences of rainfall-runoff events. For proper parameter identification, large field datasets would be needed. As these are usually not available, notably due to the randomness of the storm events, we thus propose a simple, robust and low-cost numerical method for the inverse modeling of the soil hydrodynamic properties. Among the methods, the variational data assimilation technique introduced by Le Dimet and Talagrand is applied. To that end, a variational data assimilation technique is implemented by applying automatic differentiation (AD) to augment computer codes with derivative computations. Note that very little effort is needed to obtain the differentiated code using the on-line Tapenade AD engine. Field data are collected for a three-layered CW located in Strasbourg (Alsace, France) at the water edge of the urban water stream Ostwaldergraben, during several months. Identification experiments are conducted by comparing measured and computed piezometric head by means of the least square objective function. The temporal variability of hydrodynamic parameter is then assessed and analyzed.

Keywords: automatic differentiation, constructed wetland, inverse method, mixed hybrid FEM, sensitivity analysis

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Authors: Regina A. Tayong, Reza Barati

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A stable, fast and robust three-phase, 2D IMPES simulator has been developed for assessing the influence of; breaker concentration on yield stress of filter cake and broken gel viscosity, varying polymer concentration/yield stress along the fracture face, fracture conductivity, fracture length, capillary pressure changes and formation damage on fracturing fluid cleanup in tight gas reservoirs. This model has been validated as against field data reported in the literature for the same reservoir. A 2-D, two-phase (gas/water) fracture propagation model is used to model our invasion zone and create the initial conditions for our clean-up model by distributing 200 bbls of water around the fracture. A 2-D, three-phase IMPES simulator, incorporating a yield-power-law-rheology has been developed in MATLAB to characterize fluid flow through a hydraulically fractured grid. The variation in polymer concentration along the fracture is computed from a material balance equation relating the initial polymer concentration to total volume of injected fluid and fracture volume. All governing equations and the methods employed have been adequately reported to permit easy replication of results. The effect of increasing capillary pressure in the formation simulated in this study resulted in a 10.4% decrease in cumulative production after 100 days of fluid recovery. Increasing the breaker concentration from 5-15 gal/Mgal on the yield stress and fluid viscosity of a 200 lb/Mgal guar fluid resulted in a 10.83% increase in cumulative gas production. For tight gas formations (k=0.05 md), fluid recovery increases with increasing shut-in time, increasing fracture conductivity and fracture length, irrespective of the yield stress of the fracturing fluid. Mechanical induced formation damage combined with hydraulic damage tends to be the most significant. Several correlations have been developed relating pressure distribution and polymer concentration to distance along the fracture face and average polymer concentration variation with injection time. The gradient in yield stress distribution along the fracture face becomes steeper with increasing polymer concentration. The rate at which the yield stress (τ_o) is increasing is found to be proportional to the square of the volume of fluid lost to the formation. Finally, an improvement on previous results was achieved through simulating yield stress variation along the fracture face rather than assuming constant values because fluid loss to the formation and the polymer concentration distribution along the fracture face decreases as we move away from the injection well. The novelty of this three-phase flow model lies in its ability to (i) Simulate yield stress variation with fluid loss volume along the fracture face for different initial guar concentrations. (ii) Simulate increasing breaker activity on yield stress and broken gel viscosity and the effect of (i) and (ii) on cumulative gas production within reasonable computational time.

Keywords: formation damage, hydraulic fracturing, polymer cleanup, multiphase flow numerical simulation

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Authors: Mohammad Karimi Moridani, Mohammad Abdi Zadeh, Zahra Shahiazar Mazraeh

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In recent years, the use of intelligent systems in biomedical engineering has increased dramatically, especially in the diagnosis of various diseases. Also, due to the relatively simple recording of the electrocardiogram signal (ECG), this signal is a good tool to show the function of the heart and diseases associated with it. The aim of this paper is to design an intelligent system for automatically detecting a normal electrocardiogram signal from abnormal one. Using this diagnostic system, it is possible to identify a person's heart condition in a very short time and with high accuracy. The data used in this article are from the Physionet database, available in 2016 for use by researchers to provide the best method for detecting normal signals from abnormalities. Data is of both genders and the data recording time varies between several seconds to several minutes. All data is also labeled normal or abnormal. Due to the low positional accuracy and ECG signal time limit and the similarity of the signal in some diseases with the normal signal, the heart rate variability (HRV) signal was used. Measuring and analyzing the heart rate variability with time to evaluate the activity of the heart and differentiating different types of heart failure from one another is of interest to the experts. In the preprocessing stage, after noise cancelation by the adaptive Kalman filter and extracting the R wave by the Pan and Tampkinz algorithm, R-R intervals were extracted and the HRV signal was generated. In the process of processing this paper, a new idea was presented that, in addition to using the statistical characteristics of the signal to create a return map and extraction of nonlinear characteristics of the HRV signal due to the nonlinear nature of the signal. Finally, the artificial neural networks widely used in the field of ECG signal processing as well as distinctive features were used to classify the normal signals from abnormal ones. To evaluate the efficiency of proposed classifiers in this paper, the area under curve ROC was used. The results of the simulation in the MATLAB environment showed that the AUC of the MLP and SVM neural network was 0.893 and 0.947, respectively. As well as, the results of the proposed algorithm in this paper indicated that the more use of nonlinear characteristics in normal signal classification of the patient showed better performance. Today, research is aimed at quantitatively analyzing the linear and non-linear or descriptive and random nature of the heart rate variability signal, because it has been shown that the amount of these properties can be used to indicate the health status of the individual's heart. The study of nonlinear behavior and dynamics of the heart's neural control system in the short and long-term provides new information on how the cardiovascular system functions, and has led to the development of research in this field. Given that the ECG signal contains important information and is one of the common tools used by physicians to diagnose heart disease, but due to the limited accuracy of time and the fact that some information about this signal is hidden from the viewpoint of physicians, the design of the intelligent system proposed in this paper can help physicians with greater speed and accuracy in the diagnosis of normal and patient individuals and can be used as a complementary system in the treatment centers.

Keywords: neart rate variability, signal processing, linear and non-linear features, classification methods, ROC Curve

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Authors: T. Al-Alawi, N. Shorbaji, E. Rashaidi, M.Alidrisi

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Purpose/Objective(s): The main purpose of this study is to analyze the planning of SBRT treatments for localized prostate cancer with 6FFF and 10FFF energies to see if there is a dosimetric difference between the two energies and how we can increase the plan efficiency and reduce its complexity. Also, to introduce a planning method in our department to treat prostate cancer by utilizing high energy photons without increasing patient toxicity and fulfilled all dosimetric constraints for OAR (an organ at risk). Then toevaluate the target 95% coverage PTV95, V5%, V2%, V1%, low dose volume for OAR (V1Gy, V2Gy, V5Gy), monitor unit (beam-on time), and estimate the values of homogeneity index HI, conformity index CI a Gradient index GI for each treatment plan.Materials/Methods: Two treatment plans were generated for15 patients with localized prostate cancer retrospectively using the CT planning image acquired for radiotherapy purposes. Each plan contains two/three complete arcs with two/three different collimator angle sets. The maximum dose rate available is 1400MU/min for the energy 6FFF and 2400MU/min for 10FFF. So in case, we need to avoid changing the gantry speed during the rotation, we tend to use the third arc in the plan with 6FFF to accommodate the high dose per fraction. The clinical target volume (CTV) consists of the entire prostate for organ-confined disease. The planning target volume (PTV) involves a margin of 5 mm. A 3-mm margin is favored posteriorly. Organs at risk identified and contoured include the rectum, bladder, penile bulb, femoral heads, and small bowel. The prescription dose is to deliver 35Gyin five fractions to the PTV and apply constraints for organ at risk (OAR) derived from those reported in references. Results: In terms of CI=0.99, HI=0.7, and GI= 4.1, it was observed that they are all thesame for both energies 6FFF and 10FFF with no differences, but the total delivered MUs are much less for the 10FFF plans (2907 for 6FFF vs.2468 for 10FFF) and the total delivery time is 124Sc for 6FFF vs. 61Sc for 10FFF beams. There were no dosimetric differences between 6FFF and 10FFF in terms of PTV coverage and mean doses; the mean doses for the bladder, rectum, femoral heads, penile bulb, and small bowel were collected, and they were in favor of the 10FFF. Also, we got lower V1Gy, V2Gy, and V5Gy doses for all OAR with 10FFF plans. Integral dosesID in (Gy. L) were recorded for all OAR, and they were lower with the 10FFF plans. Conclusion: High energy 10FFF has lower treatment time and lower delivered MUs; also, 10FFF showed lower integral and meant doses to organs at risk. In this study, we suggest usinga 10FFF beam for SBRTprostate treatment, which has the advantage of lowering the treatment time and that lead to lessplan complexity with respect to 6FFF beams.

Keywords: FFF beam, SBRT prostate, VMAT, prostate cancer

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Authors: Mauro Callejas-Cuervo, Andrea C. Alarcon-Aldana, Andres F. Ruiz-Olaya, Juan C. Alvarez

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Motion capture (MC) is the construction of a precise and accurate digital representation of a real motion. Systems have been used in the last years in a wide range of applications, from films special effects and animation, interactive entertainment, medicine, to high competitive sport where a maximum performance and low injury risk during training and competition is seeking. This paper presents an inertial and magnetic sensor based technological platform, intended for particular amplitude monitoring and telerehabilitation processes considering an efficient cost/technical considerations compromise. Our platform particularities offer high social impact possibilities by making telerehabilitation accessible to large population sectors in marginal socio-economic sector, especially in underdeveloped countries that in opposition to developed countries specialist are scarce, and high technology is not available or inexistent. This platform integrates high-resolution low-cost inertial and magnetic sensors with adequate user interfaces and communication protocols to perform a web or other communication networks available diagnosis service. The amplitude information is generated by sensors then transferred to a computing device with adequate interfaces to make it accessible to inexperienced personnel, providing a high social value. Amplitude measurements of the platform virtual system presented a good fit to its respective reference system. Analyzing the robotic arm results (estimation error RMSE 1=2.12° and estimation error RMSE 2=2.28°), it can be observed that during arm motion in any sense, the estimation error is negligible; in fact, error appears only during sense inversion what can easily be explained by the nature of inertial sensors and its relation to acceleration. Inertial sensors present a time constant delay which acts as a first order filter attenuating signals at large acceleration values as is the case for a change of sense in motion. It can be seen a damped response of platform virtual in other images where error analysis show that at maximum amplitude an underestimation of amplitude is present whereas at minimum amplitude estimations an overestimation of amplitude is observed. This work presents and describes the platform virtual as a motion capture system suitable for telerehabilitation with the cost - quality and precision - accessibility relations optimized. These particular characteristics achieved by efficiently using the state of the art of accessible generic technology in sensors and hardware, and adequate software for capture, transmission analysis and visualization, provides the capacity to offer good telerehabilitation services, reaching large more or less marginal populations where technologies and specialists are not available but accessible with basic communication networks.

Keywords: inertial sensors, joint amplitude measurement, MEMS, telerehabilitation

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Authors: Ines Raies, Eric Kohler, Marc Fleury, Béatrice Ledésert

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In this work, the impact of clay minerals on the formation damage of sandstone reservoirs is studied to provide a better understanding of the problem of deep geothermal reservoir permeability reduction due to fine particle dispersion and migration. In some situations, despite the presence of filters in the geothermal loop at the surface, particles smaller than the filter size (<1 µm) may surprisingly generate significant permeability reduction affecting in the long term the overall performance of the geothermal system. Our study is carried out on cores from a Triassic reservoir in the Paris Basin (Feigneux, 60 km Northeast of Paris). Our goal is to first identify the clays responsible for clogging, a mineralogical characterization of these natural samples was carried out by coupling X-Ray Diffraction (XRD), Scanning Electron Microscopy (SEM) and Energy Dispersive X-ray Spectroscopy (EDS). The results show that the studied stratigraphic interval contains mostly illite and chlorite particles. Moreover, the spatial arrangement of the clays in the rocks as well as the morphology and size of the particles, suggest that illite is more easily mobilized than chlorite by the flow in the pore network. Thus, based on these results, illite particles were prepared and used in core flooding in order to better understand the factors leading to the aggregation and deposition of this type of clay particles in geothermal reservoirs under various physicochemical and hydrodynamic conditions. First, the stability of illite suspensions under geothermal conditions has been investigated using different characterization techniques, including Dynamic Light Scattering (DLS) and Scanning Transmission Electron Microscopy (STEM). Various parameters such as the hydrodynamic radius (around 100 nm), the morphology and surface area of aggregates were measured. Then, core-flooding experiments were carried out using sand columns to mimic the permeability decline due to the injection of illite-containing fluids in sandstone reservoirs. In particular, the effects of ionic strength, temperature, particle concentration and flow rate of the injected fluid were investigated. When the ionic strength increases, a permeability decline of more than a factor of 2 could be observed for pore velocities representative of in-situ conditions. Further details of the retention of particles in the columns were obtained from Magnetic Resonance Imaging and X-ray Tomography techniques, showing that the particle deposition is nonuniform along the column. It is clearly shown that very fine particles as small as 100 nm can generate significant permeability reduction under specific conditions in high permeability porous media representative of the Triassic reservoirs of the Paris basin. These retention mechanisms are explained in the general framework of the DLVO theory

Keywords: geothermal energy, reinjection, clays, colloids, retention, porosity, permeability decline, clogging, characterization, XRD, SEM-EDS, STEM, DLS, NMR, core flooding experiments

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Authors: Eiji Nakamachi, Ryota Sakiyama, Koji Yamamoto, Yusuke Morita, Hidetoshi Sakamoto

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The regeneration of injured central nerve network caused by the cerebrovascular accidents is difficult, because of poor regeneration capability of central nerve system composed of the brain and the spinal cord. Recently, new regeneration methods such as transplant of nerve cells and supply of nerve nutritional factor were proposed and examined. However, there still remain many problems with the canceration of engrafted cells and so on and it is strongly required to establish an efficacious treating method of a central nerve system. Blackman proposed the electromagnetic stimulation method to enhance the axonal nerve extension. In this study, we try to design and fabricate a new three-dimensional (3D) bio-reactor, which can load a uniform AC magnetic field stimulation on PC12 cells in the extracellular environment for enhancement of an axonal nerve extension and 3D nerve network generation. Simultaneously, we measure the morphology of PC12 cell bodies, axons, and dendrites by the multiphoton excitation fluorescence microscope (MPM) and evaluate the effectiveness of the uniform AC magnetic stimulation to enhance the axonal nerve extension. Firstly, we designed and fabricated the uniform AC magnetic field stimulation bio-reactor. For the AC magnetic stimulation system, we used the laminated silicon steel sheets for a yoke structure of 3D chamber, which had a high magnetic permeability. Next, we adopted the pole piece structure and installed similar specification coils on both sides of the yoke. We searched an optimum pole piece structure using the magnetic field finite element (FE) analyses and the response surface methodology. We confirmed that the optimum 3D chamber structure showed a uniform magnetic flux density in the PC12 cell culture area by using FE analysis. Then, we fabricated the uniform AC magnetic field stimulation bio-reactor by adopting analytically determined specifications, such as the size of chamber and electromagnetic conditions. We confirmed that measurement results of magnetic field in the chamber showed a good agreement with FE results. Secondly, we fabricated a dish, which set inside the uniform AC magnetic field stimulation of bio-reactor. PC12 cells were disseminated with collagen gel and could be 3D cultured in the dish. The collagen gel were poured in the dish. The collagen gel, which had a disk shape of 6 mm diameter and 3mm height, was set on the membrane filter, which was located at 4 mm height from the bottom of dish. The disk was full filled with the culture medium inside the dish. Finally, we evaluated the effectiveness of the uniform AC magnetic field stimulation to enhance the nurve axonal extension. We confirmed that a 6.8 increase in the average axonal extension length of PC12 under the uniform AC magnetic field stimulation at 7 days culture in our bio-reactor, and a 24.7 increase in the maximum axonal extension length. Further, we confirmed that a 60 increase in the number of dendrites of PC12 under the uniform AC magnetic field stimulation. Finally, we confirm the availability of our uniform AC magnetic stimulation bio-reactor for the nerve axonal extension and the nerve network generation.

Keywords: nerve regeneration, axonal extension , PC12 cell, magnetic field, three-dimensional bio-reactor

Procedia PDF Downloads 168