Search results for: damage prediction

Authors: Ghada Al-Kafaji, Mohamed Sabry

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Mitochondria are the site of cellular respiration and produce energy in the form of adenosine triphosphate (ATP) via oxidative phosphorylation. They are the major source of intracellular reactive oxygen species (ROS) and are also direct target to ROS attack. Oxidative stress and ROS-mediated disruptions of mitochondrial function are major components involved in the pathogenicity of diabetic complications. In this work, the changes in mitochondrial DNA (mtDNA) copy number, biogenesis, gene expression of mtDNA-encoded subunits of electron transport chain (ETC) complexes, and mitochondrial function in response to hyperglycemia-induced ROS and the effect of direct inhibition of ROS on mitochondria were investigated in an in vitro model of diabetic nephropathy using human renal mesangial cells. The cells were exposed to normoglycemic and hyperglycemic conditions in the presence and absence of Mn(III)tetrakis(4-benzoic acid) porphyrin chloride (MnTBAP) or catalase for 1, 4 and 7 days. ROS production was assessed by the confocal microscope and flow cytometry. mtDNA copy number and PGC-1a, NRF-1, and TFAM, as well as ND2, CYTB, COI, and ATPase 6 transcripts, were all analyzed by real-time PCR. PGC-1a, NRF-1, and TFAM, as well as ND2, CYTB, COI, and ATPase 6 proteins, were analyzed by Western blotting. Mitochondrial function was determined by assessing mitochondrial membrane potential and adenosine triphosphate (ATP) levels. Hyperglycemia-induced a significant increase in the production of mitochondrial superoxide and hydrogen peroxide at day 1 (P < 0.05), and this increase remained significantly elevated at days 4 and 7 (P < 0.05). The copy number of mtDNA and expression of PGC-1a, NRF-1, and TFAM as well as ND2, CYTB, CO1 and ATPase 6 increased after one day of hyperglycemia (P < 0.05), with a significant reduction in all those parameters at 4 and 7 days (P < 0.05). The mitochondrial membrane potential decreased progressively at 1 to 7 days of hyperglycemia with the parallel progressive reduction in ATP levels over time (P < 0.05). MnTBAP and catalase treatment of cells cultured under hyperglycemic conditions attenuated ROS production reversed renal mitochondrial oxidative stress and improved mtDNA, mitochondrial biogenesis, and function. These results show that hyperglycemia-induced ROS caused an early increase in mtDNA copy number, mitochondrial biogenesis and mtDNA-encoded gene expression of the ETC subunits in human mesangial cells as a compensatory response to the decline in mitochondrial function, which precede the mtDNA defect and mitochondrial dysfunction with a progressive oxidative response. Protection from ROS-mediated damage to renal mitochondria induced by hyperglycemia may be a novel therapeutic approach for the prevention/treatment of DN.

Keywords: diabetic nephropathy, hyperglycemia, reactive oxygen species, oxidative stress, mtDNA, mitochondrial dysfunction, manganese superoxide dismutase, catalase

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Authors: Miguel Contreras, David Long, Will Bachman

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Background: Microscopy plays a central role in cell and developmental biology. In particular, fluorescence microscopy can be used to visualize specific cellular components and subsequently quantify their morphology through development of virtual-cell models for study of effects of mechanical forces on cells. However, there are challenges with these imaging experiments, which can make it difficult to quantify cell morphology: inconsistent results, time-consuming and potentially costly protocols, and limitation on number of labels due to spectral overlap. To address these challenges, the objective of this project is to develop an automatic computational machine learning pipeline to predict cellular components morphology for virtual-cell generation based on fluorescence cell membrane confocal z-stacks. Methods: Registered confocal z-stacks of nuclei and cell membrane of endothelial cells, consisting of 20 images each, were obtained from fluorescence confocal microscopy and normalized through software pipeline for each image to have a mean pixel intensity value of 0.5. An open source machine learning algorithm, originally developed to predict fluorescence labels on unlabeled transmitted light microscopy cell images, was trained using this set of normalized z-stacks on a single CPU machine. Through transfer learning, the algorithm used knowledge acquired from its previous training sessions to learn the new task. Once trained, the algorithm was used to predict morphology of nuclei using normalized cell membrane fluorescence images as input. Predictions were compared to the ground truth fluorescence nuclei images. Results: After one week of training, using one cell membrane z-stack (20 images) and corresponding nuclei label, results showed qualitatively good predictions on training set. The algorithm was able to accurately predict nuclei locations as well as shape when fed only fluorescence membrane images. Similar training sessions with improved membrane image quality, including clear lining and shape of the membrane, clearly showing the boundaries of each cell, proportionally improved nuclei predictions, reducing errors relative to ground truth. Discussion: These results show the potential of pre-trained machine learning algorithms to predict cell morphology using relatively small amounts of data and training time, eliminating the need of using multiple labels in immunofluorescence experiments. With further training, the algorithm is expected to predict different labels (e.g., focal-adhesion sites, cytoskeleton), which can be added to the automatic machine learning pipeline for direct input into Principal Component Analysis (PCA) for generation of virtual-cell mechanical models.

Keywords: cell morphology prediction, computational machine learning, fluorescence microscopy, virtual-cell models

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Authors: Maria Fontenele, Claude-Gilles Dussap, Vincent Dumouilla, Baptiste Boit

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Roquette Frères is a producer of plant-based ingredients that employs many processes to extract relevant molecules and often transforms them through chemical and physical processes to create desired ingredients with specific functionalities. In this context, Roquette encounters numerous multi-component complex systems in their processes, including fibers, proteins, and carbohydrates, in an aqueous environment. To develop, control, and optimize both new and old processes, Roquette aims to develop new in silico tools. Currently, Roquette uses process modelling tools which include specific thermodynamic models and is willing to develop computational methodologies such as molecular dynamics simulations to gain insights into the complex interactions in such complex media, and especially hydrogen bonding interactions. The issue at hand concerns aqueous mixtures of polyols with high dry matter content. The polyols mannitol and sorbitol molecules are diastereoisomers that have nearly identical chemical structures but very different physicochemical properties: for example, the solubility of sorbitol in water is 2.5 kg/kg of water, while mannitol has a solubility of 0.25 kg/kg of water at 25°C. Therefore, predicting liquid-solid equilibrium properties in this case requires sophisticated solution models that cannot be based solely on chemical group contributions, knowing that for mannitol and sorbitol, the chemical constitutive groups are the same. Recognizing the significance of solvation phenomena in polyols, the GePEB (Chemical Engineering, Applied Thermodynamics, and Biosystems) team at Institut Pascal has developed the COSMO-UCA model, which has the structural advantage of using quantum mechanics tools to predict formation and phase equilibrium properties. In this work, we use molecular dynamics simulations to elucidate the behavior of polyols in aqueous solution. Specifically, we employ simulations to compute essential metrics such as radial distribution functions and hydrogen bond autocorrelation functions. Our findings illuminate a fundamental contrast: sorbitol and mannitol exhibit disparate hydrogen bond lifetimes within aqueous environments. This observation serves as a cornerstone in elucidating the divergent physicochemical properties inherent to each compound, shedding light on the nuanced interplay between their molecular structures and water interactions. We also present a methodology to predict the physicochemical properties of complex solutions, taking as sole input the three-dimensional structure of the molecules in the medium. Finally, by developing knowledge models, we represent some physicochemical properties of aqueous solutions of sorbitol and mannitol.

Keywords: COSMO models, hydrogen bond, molecular dynamics, thermodynamics

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Authors: Pierre Tize Mha, Mohammad Jahazi, Amèvi Togne, Olivier Pantalé

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Large-size forged blocks made of medium carbon high-strength steels are extensively used in the automotive industry as dies for the production of bumpers and dashboards through the plastic injection process. The manufacturing process of the large blocks starts with ingot casting, followed by open die forging and a quench and temper heat treatment process to achieve the desired mechanical properties and numerical simulation is widely used nowadays to predict these properties before the experiment. But the temperature gradient inside the specimen remains challenging in the sense that the temperature before loading inside the material is not the same, but during the simulation, constant temperature is used to simulate the experiment because it is assumed that temperature is homogenized after some holding time. Therefore to be close to the experiment, real distribution of the temperature through the specimen is needed before the mechanical loading. Thus, We present here a robust algorithm that allows the calculation of the temperature gradient within the specimen, thus representing a real temperature distribution within the specimen before deformation. Indeed, most numerical simulations consider a uniform temperature gradient which is not really the case because the surface and core temperatures of the specimen are not identical. Another feature that influences the mechanical properties of the specimen is recrystallization which strongly depends on the deformation conditions and the type of deformation like Upsetting, Cogging...etc. Indeed, Upsetting and Cogging are the stages where the greatest deformations are observed, and a lot of microstructural phenomena can be observed, like recrystallization, which requires in-depth characterization. Complete dynamic recrystallization plays an important role in the final grain size during the process and therefore helps to increase the mechanical properties of the final product. Thus, the identification of the conditions for the initiation of dynamic recrystallization is still relevant. Also, the temperature distribution within the sample and strain rate influence the recrystallization initiation. So the development of a technique allowing to predict the initiation of this recrystallization remains challenging. In this perspective, we propose here, in addition to the algorithm allowing to get the temperature distribution before the loading stage, an analytical model leading to determine the initiation of this recrystallization. These two techniques are implemented into the Abaqus finite element software via the UAMP and VUHARD subroutines for comparison with a simulation where an isothermal temperature is imposed. The Artificial Neural Network (ANN) model to describe the plastic behavior of the material is also implemented via the VUHARD subroutine. From the simulation, the temperature distribution inside the material and recrystallization initiation is properly predicted and compared to the literature models.

Keywords: dynamic recrystallization, finite element modeling, artificial neural network, numerical implementation

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Authors: Abdoulie K. Ceesay

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Within the sequence of the whole genome, it is known that 99.9% of the human genome is similar, whilst our difference lies in just 0.1%. Among these minor dissimilarities, the most common type of genetic variations that occurs in a population is SNP, which arises due to nucleotide substitution in a protein sequence that leads to protein destabilization, alteration in dynamics, and other physio-chemical properties’ distortions. While causing variations, they are equally responsible for our difference in the way we respond to a treatment or a disease, including various cancer types. There are two types of SNPs; synonymous single nucleotide polymorphism (sSNP) and non-synonymous single nucleotide polymorphism (nsSNP). sSNP occur in the gene coding region without causing a change in the encoded amino acid, while nsSNP is deleterious due to its replacement of a nucleotide residue in the gene sequence that results in a change in the encoded amino acid. Predicting the effects of cancer related nsSNPs on protein stability, function, and dynamics is important due to the significance of phenotype-genotype association of cancer. In this thesis, Data of 5 oncogenes (ONGs) (AKT1, ALK, ERBB2, KRAS, BRAF) and 5 tumor suppressor genes (TSGs) (ESR1, CASP8, TET2, PALB2, PTEN) were retrieved from ClinVar. Five common in silico tools; Polyphen, Provean, Mutation Assessor, Suspect, and FATHMM, were used to predict and categorize nsSNPs as deleterious, benign, or neutral. To understand the impact of each variation on the phenotype, Maestro, PremPS, Cupsat, and mCSM-NA in silico structural prediction tools were used. This study comprises of in-depth analysis of 10 cancer gene variants downloaded from Clinvar. Various analysis of the genes was conducted to derive a meaningful conclusion from the data. Research done indicated that pathogenic variants are more common among ONGs. Our research also shows that pathogenic and destabilizing variants are more common among ONGs than TSGs. Moreover, our data indicated that ALK(409) and BRAF(86) has higher benign count among ONGs; whilst among TSGs, PALB2(1308) and PTEN(318) genes have higher benign counts. Looking at the individual cancer genes predisposition or frequencies of causing cancer according to our research data, KRAS(76%), BRAF(55%), and ERBB2(36%) among ONGs; and PTEN(29%) and ESR1(17%) among TSGs have higher tendencies of causing cancer. Obtained results can shed light to the future research in order to pave new frontiers in cancer therapies.

Keywords: tumor suppressor genes (TSGs), oncogenes (ONGs), non synonymous single nucleotide polymorphism (nsSNP), single nucleotide polymorphism (SNP)

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Authors: Nadeem Munawar, Tariq Mahmood, Paula Rivadeneira, Ali Akhter

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In this paper, we review on rodent species which are common inhabitants of agricultural landscapes where they are an important prey source for a wide variety of avian, reptilian, and mammalian predators. Agricultural fields are surrounded by fallow land, which provide suitable sites for shelter and breeding for rodents, while shrubs, grasses, annual weeds and forbs may provide supplementary food. The assemblage of rodent’s fauna in the cropland habitats including cropped fields, meadows and adjacent field structures like hedgerows, woodland and field margins fluctuates seasonally. The mature agricultural crops provides good source of food and shelter to the rodents and these factors along with favorable climatic factors/season facilitate breeding activities of these rodent species. Changes in vegetation height and vegetative cover affect two important aspects of a rodent’s life: food and shelter. In addition, during non-crop period vegetation can be important for building nests above or below ground and it provides thermal protection for rodents from heat and cold. The review revealed that rodents form a very diverse group of mammals, ranging from tiny pigmy mice to big capybaras, from arboreal flying squirrels to subterranean mole rats, from opportunistic omnivores (e.g. Norway rats) to specialist feeders (e.g. the North African fat sand rats that feed on a single family of plants only). It is therefore no surprise that some species thrive well under the conditions that are found in agricultural fields. The review on the population dynamics of the rodent species indicated that they are agricultural pests probably due to the heterogeneous landscape and to the high rotativity of vegetable crop cultivation. They also cause damage to various crops, directly and indirectly, by gnawing, spoilage, contamination and hoarding activities, besides this behavior they have also significance importance in agricultural habitat. The burrowing activities of rodents alter the soil properties around their burrows which improve its aeration, infiltration, increase the water holding capacity and thus encourage plant growth. These properties are beneficial for the soil because they affect absorption of phosphorus, absorption zinc, copper, other nutrients and the uptake of water and thus rodents are known as indicator species in agricultural fields. Our review suggests that wide crop field’s borders, particularly those contiguous to various cropland fields, should be understood as priority sites for nesting, feeding, and cover for the rodent’s fauna. The goal of this review paper is to provide a comprehensive synthesis of understanding regarding rodent habitat and biodiversity in agricultural landscapes.

Keywords: agricultural landscapes, food, indicator species, shelter

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Authors: N. Garrós, P. Bustos, N. Beirampour, R. Mohammadi, M. Mallandrich, A.C. Calpena, H. Colom

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Atopic dermatitis (AD) is a persistent skin condition characterized by chronic inflammation caused by an autoimmune response. It is a prevalent clinical issue that requires continual treatment to enhance the patient's quality of life. Systemic therapy often involves the use of glucocorticoids or immunosuppressants to manage symptoms. Our objective was to create and assess topical liposomal formulations containing Baricitinib (BNB), a reversible inhibitor of Janus-associated kinase (JAK), which is involved in various immune responses. These formulations were intended to address flare-ups and improve treatment outcomes for AD. We created three distinct liposomal formulations by combining different amounts of 1-palmitoyl-2-oleoyl-glycero-3-phosphocholine (POPC), cholesterol (CHOL), and ceramide (CER): (i) pure POPC, (ii) POPC mixed with CHOL (at a ratio of 8:2, mol/mol), and (iii) POPC mixed with CHOL and CER (at a ratio of 3.6:2.4:4.0 mol/mol/mol). We conducted various tests to determine the formulations' skin tolerance, irritancy capacity, and their ability to cause erythema and edema on altered skin. We also assessed the transepidermal water loss (TEWL) and skin hydration of rabbits to evaluate the efficacy of the formulations. Histological analysis, the HET-CAM test, and the modified Draize test were all used in the evaluation process. The histological analysis revealed that liposome POPC and POPC:CHOL avoided any damage to the tissues structures. The HET-CAM test showed no irritation effect caused by any of the three liposomes, and the modified Draize test showed a good Draize score for erythema and edema. Liposome POPC effectively counteracted the impact of xylol on the skin, and no erythema or edema was observed during the study. TEWL values were constant for all the liposomes with similar values to the negative control (within the range 8 - 15 g/h·m2, which means a healthy value for rabbits), whereas the positive control showed a significant increase. The skin hydration values were constant and followed the trend of the negative control, while the positive control showed a steady increase during the tolerance study. In conclusion, the developed formulations containing BNB exhibited no harmful or irritating effects, they did not demonstrate any irritant potential in the HET-CAM test and liposomes POPC and POPC:CHOL did not cause any structural alteration according to the histological analysis. These positive findings suggest that additional research is necessary to evaluate the efficacy of these liposomal formulations in animal models of the disease, including mutant animals. Furthermore, before proceeding to clinical trials, biochemical investigations should be conducted to better understand the mechanisms of action involved in these formulations.

Keywords: baricitinib, HET-CAM test, histological study, JAK inhibitor, liposomes, modified draize test

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Authors: Mohammed El Raey, Moustafa Osman Mohammed

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The spatial-ecological modeling is relating sustainable dispersions with social development. Sustainability with spatial-ecological model gives attention to urban environments in the design review management to comply with Earth’s System. Naturally exchange patterns of ecosystems have consistent and periodic cycles to preserve energy flows and materials in Earth’s System. The probabilistic risk assessment (PRA) technique is utilized to assess the safety of industrial complex. The other analytical approach is the Failure-Safe Mode and Effect Analysis (FMEA) for critical components. The plant safety parameters are identified for engineering topology as employed in assessment safety of industrial ecology. In particular, the most severe accidental release of hazardous gaseous is postulated, analyzed and assessment in industrial region. The IAEA- safety assessment procedure is used to account the duration and rate of discharge of liquid chlorine. The ecological model of plume dispersion width and concentration of chlorine gas in the downwind direction is determined using Gaussian Plume Model in urban and ruler areas and presented with SURFER®. The prediction of accident consequences is traced in risk contour concentration lines. The local greenhouse effect is predicted with relevant conclusions. The spatial-ecological model is also predicted the distribution schemes from the perspective of pollutants that considered multiple factors of multi-criteria analysis. The data extends input–output analysis to evaluate the spillover effect, and conducted Monte Carlo simulations and sensitivity analysis. Their unique structure is balanced within “equilibrium patterns”, such as the biosphere and collective a composite index of many distributed feedback flows. These dynamic structures are related to have their physical and chemical properties and enable a gradual and prolonged incremental pattern. While this spatial model structure argues from ecology, resource savings, static load design, financial and other pragmatic reasons, the outcomes are not decisive in artistic/ architectural perspective. The hypothesis is an attempt to unify analytic and analogical spatial structure for development urban environments using optimization software and applied as an example of integrated industrial structure where the process is based on engineering topology as optimization approach of systems ecology.

Keywords: spatial-ecological modeling, spatial structure orientation impact, composite structure, industrial ecology

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Authors: A. Alyaaria, b, J. P. Wignerona, A. Ducharneb, Y. Kerrc, P. de Rosnayd, R. de Jeue, A. Govinda, A. Al Bitarc, C. Albergeld, J. Sabaterd, C. Moisya, P. Richaumec, A. Mialonc

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Global Level-3 surface soil moisture (SSM) maps from the passive microwave soil moisture and Ocean Salinity satellite (SMOSL3) have been released. To further improve the Level-3 retrieval algorithm, evaluation of the accuracy of the spatio-temporal variability of the SMOS Level 3 products (referred to here as SMOSL3) is necessary. In this study, a comparative analysis of SMOSL3 with a SSM product derived from the observations of the Advanced Microwave Scanning Radiometer (AMSR-E) computed by implementing the Land Parameter Retrieval Model (LPRM) algorithm, referred to here as AMSRM, is presented. The comparison of both products (SMSL3 and AMSRM) were made against SSM products produced by a numerical weather prediction system (SM-DAS-2) at ECMWF (European Centre for Medium-Range Weather Forecasts) for the 03/2010-09/2011 period at global scale. The latter product was considered here a 'reference' product for the inter-comparison of the SMOSL3 and AMSRM products. Three statistical criteria were used for the evaluation, the correlation coefficient (R), the root-mean-squared difference (RMSD), and the bias. Global maps of these criteria were computed, taking into account vegetation information in terms of biome types and Leaf Area Index (LAI). We found that both the SMOSL3 and AMSRM products captured well the spatio-temporal variability of the SM-DAS-2 SSM products in most of the biomes. In general, the AMSRM products overestimated (i.e., wet bias) while the SMOSL3 products underestimated (i.e., dry bias) SSM in comparison to the SM-DAS-2 SSM products. In term of correlation values, the SMOSL3 products were found to better capture the SSM temporal dynamics in highly vegetated biomes ('Tropical humid', 'Temperate Humid', etc.) while best results for AMSRM were obtained over arid and semi-arid biomes ('Desert temperate', 'Desert tropical', etc.). When removing the seasonal cycles in the SSM time variations to compute anomaly values, better correlation with the SM-DAS-2 SSM anomalies were obtained with SMOSL3 than with AMSRM, in most of the biomes with the exception of desert regions. Eventually, we showed that the accuracy of the remotely sensed SSM products is strongly related to LAI. Both the SMOSL3 and AMSRM (slightly better) SSM products correlate well with the SM-DAS2 products over regions with sparse vegetation for values of LAI < 1 (these regions represent almost 50% of the pixels considered in this global study). In regions where LAI>1, SMOSL3 outperformed AMSRM with respect to SM-DAS-2: SMOSL3 had almost consistent performances up to LAI = 6, whereas AMSRM performance deteriorated rapidly with increasing values of LAI.

Keywords: remote sensing, microwave, soil moisture, AMSR-E, SMOS

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Authors: Fabiana Franceschi, Martha Cobo, Manuel Figueredo

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Bogotá, the capital of Colombia, is its largest city and one of the most polluted in Latin America due to the fast economic growth over the last ten years. Bogotá has been affected by high pollution events which led to the high concentration of PM10 and NO2, exceeding the local 24-hour legal limits (100 and 150 g/m3 each). The most important pollutants in the city are PM10 and PM2.5 (which are associated with respiratory and cardiovascular problems) and it is known that their concentrations in the atmosphere depend on the local meteorological factors. Therefore, it is necessary to establish a relationship between the meteorological variables and the concentrations of the atmospheric pollutants such as PM10, PM2.5, CO, SO2, NO2 and O3. This study aims to determine the interrelations between meteorological variables and air pollutants in Bogotá, using data mining techniques. Data from 13 monitoring stations were collected from the Bogotá Air Quality Monitoring Network within the period 2010-2015. The Principal Component Analysis (PCA) algorithm was applied to obtain primary relations between all the parameters, and afterwards, the K-means clustering technique was implemented to corroborate those relations found previously and to find patterns in the data. PCA was also used on a per shift basis (morning, afternoon, night and early morning) to validate possible variation of the previous trends and a per year basis to verify that the identified trends have remained throughout the study time. Results demonstrated that wind speed, wind direction, temperature, and NO2 are the most influencing factors on PM10 concentrations. Furthermore, it was confirmed that high humidity episodes increased PM2,5 levels. It was also found that there are direct proportional relationships between O3 levels and wind speed and radiation, while there is an inverse relationship between O3 levels and humidity. Concentrations of SO2 increases with the presence of PM10 and decreases with the wind speed and wind direction. They proved as well that there is a decreasing trend of pollutant concentrations over the last five years. Also, in rainy periods (March-June and September-December) some trends regarding precipitations were stronger. Results obtained with K-means demonstrated that it was possible to find patterns on the data, and they also showed similar conditions and data distribution among Carvajal, Tunal and Puente Aranda stations, and also between Parque Simon Bolivar and las Ferias. It was verified that the aforementioned trends prevailed during the study period by applying the same technique per year. It was concluded that PCA algorithm is useful to establish preliminary relationships among variables, and K-means clustering to find patterns in the data and understanding its distribution. The discovery of patterns in the data allows using these clusters as an input to an Artificial Neural Network prediction model.

Keywords: air pollution, air quality modelling, data mining, particulate matter

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Authors: Bastien Sanglard, Lou Magnat, Ligia Barna, Julian Carrey, Sébastien Lachaize

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Cooking is a primary need for humans, several techniques being used around the globe based on different sources of energy: electricity, solid fuel (wood, coal...), fuel or liquefied petroleum gas. However, all of them leads to direct or indirect greenhouse gas emissions and sometimes health damage in household. Therefore, the solar concentrated power represent a great option to lower the damages because of a cleaner using phase. Nevertheless, the construction phase of the solar cooker still requires primary energy and materials, which leads to environmental impacts. The aims of this work is to analyse the ecological impacts of a commercialaluminium parabola and to compare it with other means of cooking, taking the boiling of 2 litres of water three times a day during 40 years as the functional unit. Life cycle assessment was performed using the software Umberto and the EcoInvent database. Calculations were realized over more than 13 criteria using two methods: the international panel on climate change method and the ReCiPe method. For the reflector itself, different aluminium provenances were compared, as well as the use of recycled aluminium. For the structure, aluminium was compared to iron (primary and recycled) and wood. Results show that climate impacts of the studied parabola was 0.0353 kgCO2eq/kWh when built with Chinese aluminium and can be reduced by 4 using aluminium from Canada. Assessment also showed that using 32% of recycled aluminium would reduce the impact by 1.33 and 1.43 compared to the use of primary Canadian aluminium and primary Chinese aluminium, respectively. The exclusive use of recycled aluminium lower the impact by 17. Besides, the use of iron (recycled or primary) or wood for the structure supporting the reflector significantly lowers the impact. The impact categories of the ReCiPe method show that the parabola made from Chinese aluminium has the heaviest impact - except for metal resource depletion - compared to aluminium from Canada, recycled aluminium or iron. Impact of solar cooking was then compared to gas stove and induction. The gas stove model was a cast iron tripod that supports the cooking pot, and the induction plate was as well a single spot plate. Results show the parabolic solar cooker has the lowest ecological impact over the 13 criteria of the ReCiPe method and over the global warming potential compared to the two other technologies. The climate impact of gas cooking is 0.628kgCO2/kWh when used with natural gas and 0.723 kgCO2/kWh when used with a bottle of gas. In each case, the main part of emissions came from gas burning. Induction cooking has a global warming potential of 0.12 kgCO2eq/kWh with the electricity mix of France, 96.3% of the impact being due to electricity production. Therefore, the electricity mix is a key factor for this impact: for instance, with the electricity mix of Germany and Poland, impacts are 0.81kgCO2eq/kWh and 1.39 kgCO2eq/kWh, respectively. Therefore, the parabolic solar cooker has a real ecological advantages compared to both gas stove and induction plate.

Keywords: life cycle assessement, solar concentration, cooking, sustainability

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Authors: N. Szczepanska, B. Kudlak, G. Yotova, S. Tsakovski, J. Namiesnik

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In the scientific literature related to the widely understood issue of packaging materials designed to have contact with food (food contact materials), there is much information on raw materials used for their production, as well as their physiochemical properties, types, and parameters. However, not much attention is given to the issues concerning migration of toxic substances from packaging and its actual influence on the health of the final consumer, even though health protection and food safety are the priority tasks. The goal of this study was to estimate the impact of particular foodstuff packaging type, food production, and storage conditions on the degree of leaching of potentially toxic compounds and endocrine disruptors to foodstuffs using the acute toxicity test Microtox and XenoScreen YES YAS assay. The selected foodstuff packaging materials were metal cans used for fish storage and tetrapak. Five stimulants respectful to specific kinds of food were chosen in order to assess global migration: distilled water for aqueous foods with a pH above 4.5; acetic acid at 3% in distilled water for acidic aqueous food with pH below 4.5; ethanol at 5% for any food that may contain alcohol; dimethyl sulfoxide (DMSO) and artificial saliva were used in regard to the possibility of using it as an simulation medium. For each packaging three independent variables (temperature and contact time) factorial design simulant was performed. Xenobiotics migration from epoxy resins was studied at three different temperatures (25°C, 65°C, and 121°C) and extraction time of 12h, 48h and 2 weeks. Such experimental design leads to 9 experiments for each food simulant as conditions for each experiment are obtained by combination of temperature and contact time levels. Each experiment was run in triplicate for acute toxicity and in duplicate for estrogen disruption potential determination. Multi-factor analysis of variation (MANOVA) was used to evaluate the effects of the three main factors solvent, temperature (temperature regime for cup), contact time and their interactions on the respected dependent variable (acute toxicity or estrogen disruption potential). From all stimulants studied the most toxic were can and tetrapak lining acetic acid extracts that are indication for significant migration of toxic compounds. This migration increased with increase of contact time and temperature and justified the hypothesis that food products with low pH values cause significant damage internal resin filling. Can lining extracts of all simulation medias excluding distilled water and artificial saliva proved to contain androgen agonists even at 25°C and extraction time of 12h. For tetrapak extracts significant endocrine potential for acetic acid, DMSO and saliva were detected.

Keywords: food packaging, extraction, migration, toxicity, biotest

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Authors: Uchenna Nkiruka Umeononihu, Adenike Kuku, Oludele Odekanyin, Olubunmi Babalola, Femi Agboola, Rapheal Okonji

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In this study, a lectin from the bulb of Dioscorea bulbifera was purified, characterised, and its acute and sub-acute toxicity was investigated with a view to evaluate its toxic effects in mice. The protein from the bulb was extracted by homogenising 50 g of the bulb in 500 ml of phosphate buffered saline (0.025 M) of pH 7.2, stirred for 3 hr, and centrifuged at the speed of 3000 rpm. Blood group and sugar specificity assays of the crude extract were determined. The lectin was purified in a two-step procedure- gel filtration on Sephadex G-75 and affinity chromatography on Sepharose 4-B arabinose. The degree of purity of the purified lectin was ascertained by SDS-polyacrylamide gel electrophoresis. Detection of covalently bound carbohydrate was carried out with Periodic Acid-Schiffs (PAS) reagent staining technique. Effects of temperature, pH, and EDTA on the lectin were carried out using standard methods. This was followed by acute toxicity studies via oral and subcutaneous routes using mice. The animals were monitored for mortality and signs of toxicity. The sub-acute toxicity studies were carried out using rats. Different concentrations of the lectin were administered twice daily for 5 days via the subcutaneous route. The animals were sacrificed on the sixth day; blood samples and liver tissues were collected. Biochemical assays (determination of total protein, direct bilirubin, Alanine aminotransferase (ALT), Aspartate aminotransferase (AST), catalase (CAT), and superoxide dismutase (SOD)) were carried out on the serum and liver homogenates. The collected organs (heart, liver, kidney, and spleen) were subjected to histopathological analysis. The results showed that lectin from the bulbs of Dioscorea bulbifera agglutinated non-specifically the erythrocytes of the human ABO system as well as rabbit erythrocytes. The haemagglutinating activity was strongly inhibited by arabinose and dulcitol with minimum inhibitory concentrations of 0.781 and 6.25, respectively. The lectin was purified to homogeneity with native and subunit molecular weights of 56,273 and 29,373 Daltons, respectively. The lectin was thermostable up to 30 0C and lost 25 %, 33.3 %, and 100 % of its heamagglutinating activity at 40°C, 50°C, and 60°C, respectively. The lectin was maximally active at pH 4 and 5 but lost its total activity at pH eight, while EDTA (10 mM) had no effect on its haemagglutinating activity. PAS reagent staining showed that the lectin was not a glycoprotein. The sub-acute studies on rats showed elevated levels of ALT, AST, serum bilirubin, total protein in serum and liver homogenates suggesting damage to liver and spleen. The study concluded that the aerial bulb of D. bulbifera lectin was non-specific in its heamagglutinating activity and dimeric in its structure. The lectin shared some physicochemical characteristics with lectins from other Dioscorecea species and was moderately toxic to the liver and spleen of treated animals.

Keywords: Dioscorea bulbifera, heamagglutinin, lectin, toxicity

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Authors: Irina Veselova, Maria Makedonskaya, Olga Eremina, Alexandr Sidorov, Eugene Goodilin, Tatyana Shekhovtsova

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Such catecholamines as dopamine, norepinephrine, and epinephrine are the principal neurotransmitters in the sympathetic nervous system. Catecholamines and their metabolites are considered to be important markers of socially significant diseases such as atherosclerosis, diabetes, coronary heart disease, carcinogenesis, Alzheimer's and Parkinson's diseases. Currently, neurotransmitters can be studied via electrochemical and chromatographic techniques that allow their characterizing and quantification, although these techniques can only provide crude spatial information. Besides, the difficulty of catecholamine determination in biological materials is associated with their low normal concentrations (~ 1 nM) in biomaterials, which may become even one more order lower because of some disorders. In addition, in blood they are rapidly oxidized by monoaminooxidases from thrombocytes and, for this reason, the determination of neurotransmitter metabolism indicators in an organism should be very rapid (15—30 min), especially in critical states. Unfortunately, modern instrumental analysis does not offer a complex solution of this problem: despite its high sensitivity and selectivity, HPLC-MS cannot provide sufficiently rapid analysis, while enzymatic biosensors and immunoassays for the determination of the considered analytes lack sufficient sensitivity and reproducibility. Fluorescent and SERS-sensors remain a compelling technology for approaching the general problem of selective neurotransmitter detection. In recent years, a number of catecholamine sensors have been reported including RNA aptamers, fluorescent ribonucleopeptide (RNP) complexes, and boronic acid based synthetic receptors and the sensor operated in a turn-off mode. In this work we present the fluorescent and SERS turn-on sensor systems based on the bio- or chemorecognizing nanostructured films {chitosan/collagen-Tb/Eu/Cu-nanoparticles-indicator reagents} that provide the selective recognition, visualization, and sensing of the above mentioned catecholamines on the level of nanomolar concentrations in biomaterials (cell cultures, tissue etc.). We have (1) developed optically transparent porous films and gels of chitosan/collagen; (2) ensured functionalization of the surface by molecules-'recognizers' (by impregnation and immobilization of components of the indicator systems: biorecognizing and auxiliary reagents); (3) performed computer simulation for theoretical prediction and interpretation of some properties of the developed materials and obtained analytical signals in biomaterials. We are grateful for the financial support of this research from Russian Foundation for Basic Research (grants no. 15-03-05064 a, and 15-29-01330 ofi_m).

Keywords: biomaterials, fluorescent and SERS-recognition, neurotransmitters, solid-phase turn-on sensor system

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Authors: Christian Lauter, Corin Reuter, Shuang Wu, Thomas Troester

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Lightweight construction became more and more important over the last decades in several applications, e.g. in the automotive or aircraft sector. This is the result of economic and ecological constraints on the one hand and increasing safety and comfort requirements on the other hand. In the field of lightweight design, different approaches are used due to specific requirements towards the technical systems. The use of endless carbon fiber reinforced plastics (CFRP) offers the largest weight saving potential of sometimes more than 50% compared to conventional metal-constructions. However, there are very limited industrial applications because of the cost-intensive manufacturing of the fibers and production technologies. Other disadvantages of pure CFRP-structures affect the quality control or the damage resistance. One approach to meet these challenges is hybrid materials. This means CFRP and sheet metal are combined on a material level. Therefore, new opportunities for innovative process routes are realizable. Hybrid lightweight design results in lower costs due to an optimized material utilization and the possibility to integrate the structures in already existing production processes of automobile manufacturers. In recent and current research, the advantages of two-layered hybrid materials have been pointed out, i.e. the possibility to realize structures with tailored mechanical properties or to divide the curing cycle of the epoxy resin into two steps. Current research work at the Chair for Automotive Lightweight Design (LiA) at the Paderborn University focusses on production processes for fiber-metal-laminates. The aim of this work is the development and qualification of a large-scale production process for high-performance fiber-metal-laminates (FML) for industrial applications in the automotive or aircraft sector. Therefore, the prepreg-press-technology is used, in which pre-impregnated carbon fibers and sheet metals are formed and cured in a closed, heated mold. The investigations focus e.g. on the realization of short process chains and cycle times, on the reduction of time-consuming manual process steps, and the reduction of material costs. This paper gives an overview over the considerable steps of the production process in the beginning. Afterwards experimental results are discussed. This part concentrates on the influence of different process parameters on the mechanical properties, the laminate quality and the identification of process limits. Concluding the advantages of this technology compared to conventional FML-production-processes and other lightweight design approaches are carried out.

Keywords: composite material, fiber-metal-laminate, lightweight construction, prepreg-press-technology, large-series production

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Authors: Nathaniel Oladimeji Dixon, Adekemi Dorcas Fadun

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Educational managers have observed a downward trend in the administrative effectiveness of non-teaching staff in federal universities in South-west Nigeria. This is evident in the low-quality service delivery of administrators and unaccomplished institutional goals and missions of higher education. Scholars have thus indicated the need for the deployment and adoption of a practice that encourages information collection and sharing among stakeholders with a view to improving service delivery and outcomes. This study examined the extent to which knowledge management correlated with the administrative effectiveness of non-teaching staff in federal universities in South-west Nigeria. The study adopted the survey design. Three federal universities (the University of Ibadan, Federal University of Agriculture, Abeokuta, and Obafemi Awolowo University) were purposively selected because administrative ineffectiveness was more pronounced among non-teaching staff in government-owned universities, and these federal universities were long established. The proportional and stratified random sampling was adopted to select 1156 non-teaching staff across the three universities along the three existing layers of the non-teaching staff: secretarial (senior=311; junior=224), non-secretarial (senior=147; junior=241) and technicians (senior=130; junior=103). Knowledge Management Practices Questionnaire with four sub-scales: knowledge creation (α=0.72), knowledge utilization (α=0.76), knowledge sharing (α=0.79) and knowledge transfer (α=0.83); and Administrative Effectiveness Questionnaire with four sub-scales: communication (α=0.84), decision implementation (α=0.75), service delivery (α=0.81) and interpersonal relationship (α=0.78) were used for data collection. Data were analyzed using descriptive statistics, Pearson product-moment correlation and multiple regression at 0.05 level of significance, while qualitative data were content analyzed. About 59.8% of the non-teaching staff exhibited a low level of knowledge management. The indices of administrative effectiveness of non-teaching staff were rated as follows: service delivery (82.0%), communication (78.0%), decision implementation (71.0%) and interpersonal relationship (68.0%). Knowledge management had significant relationships with the indices of administrative effectiveness: service delivery (r=0.82), communication (r=0.81), decision implementation (r=0.80) and interpersonal relationship (r=0.47). Knowledge management had a significant joint prediction on administrative effectiveness (F (4;1151)= 0.79, R=0.86), accounting for 73.0% of its variance. Knowledge sharing (β=0.38), knowledge transfer (β=0.26), knowledge utilization (β=0.22), and knowledge creation (β=0.06) had relatively significant contributions to administrative effectiveness. Lack of team spirit and withdrawal syndrome is the major perceived constraints to knowledge management practices among the non-teaching staff. Knowledge management positively influenced the administrative effectiveness of the non-teaching staff in federal universities in South-west Nigeria. There is a need to ensure that the non-teaching staff imbibe team spirit and embrace teamwork with a view to eliminating their withdrawal syndromes. Besides, knowledge management practices should be deployed into the administrative procedures of the university system.

Keywords: knowledge management, administrative effectiveness of non-teaching staff, federal universities in the south-west of nigeria., knowledge creation, knowledge utilization, effective communication, decision implementation

Procedia PDF Downloads 64

Authors: Sthephanie A. Colmenares, Fabio A. Rojas, Pablo A. Arbeláez, Johann F. Osma, Diana Narvaez

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The loss of functional tissue is a ubiquitous and expensive health care problem, with very limited treatment options for these patients. The golden standard for large bone damage is a cadaveric bone as an allograft with stainless steel support; however, this solution only applies to bones with simple morphologies (long bones), has a limited material supply and presents long term problems regarding mechanical strength, integration, differentiation and induction of native bone tissue. Therefore, the fabrication of a scaffold with biological, physical and chemical properties similar to the human bone with a fabrication method for morphology manipulation is the focus of this investigation. Towards this goal, an alginate and coral matrix was created using two production techniques; the coral was chosen because of its chemical composition and the alginate due to its compatibility and mechanical properties. In order to construct the coral alginate scaffold the following methodology was employed; cleaning of the coral, its pulverization, scaffold fabrication and finally the mechanical and biological characterization. The experimental design had: mill method and proportion of alginate and coral, as the two factors, with two and three levels each, using 5 replicates. The coral was cleaned with sodium hypochlorite and hydrogen peroxide in an ultrasonic bath. Then, it was milled with both a horizontal and a ball mill in order to evaluate the morphology of the particles obtained. After this, using a combination of alginate and coral powder and water as a binder, scaffolds of 1cm3 were printed with a SpectrumTM Z510 3D printer. This resulted in solid cubes that were resistant to small compression stress. Then, using a ESQUIM DP-143 silicon mold, constructs used for the mechanical and biological assays were made. An INSTRON 2267® was implemented for the compression tests; the density and porosity were calculated with an analytical balance and the biological tests were performed using cell cultures with VERO fibroblast, and Scanning Electron Microscope (SEM) as visualization tool. The Young’s moduli were dependent of the pulverization method, the proportion of coral and alginate and the interaction between these factors. The maximum value was 5,4MPa for the 50/50 proportion of alginate and horizontally milled coral. The biological assay showed more extracellular matrix in the scaffolds consisting of more alginate and less coral. The density and porosity were proportional to the amount of coral in the powder mix. These results showed that this composite has potential as a biomaterial, but its behavior is elastic with a small Young’s Modulus, which leads to the conclusion that the application may not be for long bones but for tissues similar to cartilage.

Keywords: alginate, biomaterial, bone engineering, coral, Porites asteroids, SEM

Procedia PDF Downloads 237

Authors: Mahmut Sozmen, Alparslan Kadir Devrim, Yonca Betil Kabak, Tuba Devrim

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Acute myocardial infarction is the leading cause of deaths in the worldwide. Mature cardiomyocytes do not have the ability to regenerate instead fibrous tissue proliferate and granulation tissue to fill out. Periostin is an extracellular matrix protein from fasciclin family and it plays an important role in the cell adhesion, migration, and growth of the organism. Periostin prevents apoptosis while stimulating cardiomyocytes. The main objective of this project is to investigate the effects of the recombinant murine periostin peptide administration for the cardiomyocyte regeneration in a rat model of acute myocardial infarction. The experiment was performed on 84 male rats (6 months old) in 4 group each contains 21 rats. Saline applied subcutaneously (1 ml/kg) two times with 24 hours intervals to the rats in control group (Group 1). Recombinant periostin peptide (1 μg/kg) dissolved in saline applied intraperitoneally in group 2 on 1, 3, 7, 14 and 21. days on same dates in group 4. Isoproterenol dissolved in saline applied intraperitoneally (85mg/kg/day) two times with 24 hours intervals to the groups 3 and 4. Rats in group 4 further received recombinant periostin peptide (1 μg/kg) dissolved in saline intraperitoneally starting one day after the final isoproterenol administration on days 1, 3, 7, 14 and 21. Following the final application of periostin rats continued to feed routinely with pelleted chow and water ad libitum for further seven days. At the end of 7th day rats sacrificed, blood and heart tissue samples collected for the immunohistochemical and biochemical analysis. Angiogenesis in response to tissue damage, is a highly dynamic process regulated by signals from the surrounding extracellular matrix and blood serum. In this project, VEGF, ANGPT, bFGF, TGFβ are the key factors that contribute to cardiomyocyte regeneration were investigated. Additionally, the relationship between mitosis and apoptosis (Bcl-2, Bax, PCNA, Ki-67, Phopho-Histone H3), cell cycle activators and inhibitors (Cyclin D1, D2, A2, Cdc2), the origin of regenerating cells (cKit and CD45) were examined. Present results revealed that periostin stimulated cardiomyocye cell-cycle re-entry in both normal and MCA damaged cardiomyocytes and increased angiogenesis. Thus, periostin contributes to cardiomyocyte regeneration during the healing period following myocardial infarction which provides a better understanding of its role of this mechanism, improving recovery rates and it is expected to contribute the lack of literature on this subject. Acknowledgement: This project was financially supported by Turkish Scientific Research Council- Agriculture, Forestry and Veterinary Research Support Group (TUBİTAK-TOVAG; Project No: 114O734), Ankara, TURKEY.

Keywords: cardiotoxicity, immunohistochemistry, isoproterenol, periostin

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Authors: Alessandra Pardu, Elena Curti, Marco Caredda, Alessio Dedola, Margherita Addis, Massimo Pes, Antonio Pirisi, Tonina Roggio, Sergio Uzzau, Roberto Anedda

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Some of the artisanal cheeses products of European Countries certificated as PDO (Protected Designation of Origin) are made from raw milk. To recognise potential frauds (e.g. pasteurisation or thermisation of milk aimed at raw milk cheese production), the alkaline phosphatase (ALP) assay is currently applied only for pasteurisation, although it is known to have notable limitations for the validation of ALP enzymatic state in nonbovine milk. It is known that frauds considerably impact on customers and certificating institutions, sometimes resulting in a damage of the product image and potential economic losses for cheesemaking producers. Robust, validated, and univocal analytical methods are therefore needed to allow Food Control and Security Organisms, to recognise a potential fraud. In an attempt to develop a new reliable method to overcome this issue, Time-Domain Nuclear Magnetic Resonance (TD-NMR) spectroscopy has been applied in the described work. Daily fresh milk was analysed raw (680.00 µL in each 10-mm NMR glass tube) at least in triplicate. Thermally treated samples were also produced, by putting each NMR tube of fresh raw milk in water pre-heated at temperatures from 68°C up to 72°C and for up to 3 min, with continuous agitation, and quench-cooled to 25°C in a water and ice solution. Raw and thermally treated samples were analysed in terms of 1H T2 transverse relaxation times with a CPMG sequence (Recycle Delay: 6 s, interpulse spacing: 0.05 ms, 8000 data points) and quasi-continuous distributions of T2 relaxation times were obtained by CONTIN analysis. In line with previous data collected by high field NMR techniques, a decrease in the spin-spin relaxation constant T2 of the predominant 1H population was detected in heat-treated milk as compared to raw milk. The decrease of T2 parameter is consistent with changes in chemical exchange and diffusive phenomena, likely associated to changes in milk protein (i.e. whey proteins and casein) arrangement promoted by heat treatment. Furthermore, experimental data suggest that molecular alterations are strictly dependent on the specific heat treatment conditions (temperature/time). Such molecular variations in milk, which are likely transferred to cheese during cheesemaking, highlight the possibility to extend the TD-NMR technique directly on cheese to develop a method for assessing a fraud related to the use of a milk thermal treatment in PDO raw milk cheese. Results suggest that TDNMR assays might pave a new way to the detailed characterisation of heat treatments of milk.

Keywords: cheese fraud, milk, pasteurisation, TD-NMR

Procedia PDF Downloads 213

Authors: Apurva Singh, S. P. Jaiswar, Apala Priyadarshini, Akancha Pandey

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Objective: The aim of this study is to find the association of PON1 gene polymorphism with pesticides In RPL subjects. Background: Recurrent pregnancy loss (RPL) is defined as three or more sequential abortions before the 20th week of gestation. Pesticides and its derivatives (organochlorine and organophosphate) are proposed to accommodate a ruler chemical for RPL in the sub-humid region of India. The paraoxonase-1 enzyme (PON1) plays an important role in the toxicity of some organophosphate pesticides, with low PON1 activity being associated with higher pesticide sensitivity Methodology: This is a case-control study done in Department of Obstetrics & Gynaecology & Department of Biochemistry, K.G.M.U, Lucknow, India. The subjects were enrolled after fulfilling the inclusion & exclusion criteria. Inclusion criteria: Cases- Subject having two or more spontaneous abortions & Control- Healthy female having one or more alive child was selected. Exclusion criteria: Cases & Control- Subject having the following disease will be excluded from the study Diabetes mellitus, Hypertension, Tuberculosis, Immunocompromised patients, any endocrine disorder and genital, colon or breast cancer any other malignancies. Blood samples were collected in EDTA tubes from cases & healthy control women & genomic DNA was extracted by phenol-chloroform method. The estimation of pesticides residue from blood was done by HPLC. Biochemical estimation was also performed. Genotyping of PON1 gene polymorphism was performed by RFLP. Statistical analysis of the data was performed using the SPSS16.3 software. Results: A sum of total 14 pesticides (12 organochlorine and 2 organophosphate) selected on the basis of their persistent nature and consumption rate. The significant level of pesticide (ppb) estimated by the Mann whiney test and it was found to be significant at higher level of β-HCH (p:0.04), γ-HCH (p:0.001), δ-HCH (p: 0.002), chloropyrifos (p:0.001), pp-DDD (p:0.001) and fenvalrate (p: 0.001) in case group compare to its control. The level of antioxidant enzymes were found to be significantly decreased among the cases. Wild homozygous TT was more frequent and prevalent among control groups. However, heterozygous group (Tt) was more in cases than control groups (CI-0.3-1.3) (p=0.06). Conclusion: Higher levels of pesticides with endocrine disrupting potential in cases indicate the possible role of these compounds as one of the causes of recurrent pregnancy loss. Possibly, increased pesticide level appears to indicate increased levels of oxidative damage that has been associated with the possible cause of Recurrent Miscarriage, it may reflect indirect evidence of toxicity rather than the direct cause. Since both factors are reported to increase risk, individuals with higher levels of these 'Toxic compounds' especially in 'high-risk genotypes' might be more susceptible to recurrent pregnancy loss.

Keywords: paraoxonase, pesticides, PON1, RPL

Procedia PDF Downloads 119

Authors: Richa Sharma, Uma Nahar, Sadhna Sharma, Indu Verma

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Counteracting the deadly pathogen Mycobacterium tuberculosis (M. tb) effectively is still a global challenge. Scrutinizing alternative weapons like antimicrobial peptides to strengthen existing tuberculosis artillery is urgently required. Considering the antimycobacterial potential of Human Beta Defensin 1 (HBD-1) along with isoniazid, the present study was designed to explore the ability of HBD-1 to act against active and dormant M. tb. HBD-1 was screened in silico using antimicrobial peptide prediction servers to identify its short antimicrobial motif. The activity of both HBD-1 and its selected motif (Pep B) was determined at different concentrations against actively growing M. tb in vitro and ex vivo in monocyte derived macrophages (MDMs). Log phase M. tb was grown along with HBD-1 and Pep B for 7 days. M. tb infected MDMs were treated with HBD-1 and Pep B for 72 hours. Thereafter, colony forming unit (CFU) enumeration was performed to determine activity of both peptides against actively growing in vitro and intracellular M. tb. The dormant M. tb models were prepared by following two approaches and treated with different concentrations of HBD-1 and Pep B. Firstly, 20-22 days old M. tbH37Rv was grown in potassium deficient Sauton media for 35 days. The presence of dormant bacilli was confirmed by Nile red staining. Dormant bacilli were further treated with rifampicin, isoniazid, HBD-1 and its motif for 7 days. The effect of both peptides on latent bacilli was assessed by colony forming units (CFU) and most probable number (MPN) enumeration. Secondly, human PBMC granuloma model was prepared by infecting PBMCs seeded on collagen matrix with M. tb(MOI 0.1) for 10 days. Histopathology was done to confirm granuloma formation. The granuloma thus formed was incubated for 72 hours with rifampicin, HBD-1 and Pep B individually. Difference in bacillary load was determined by CFU enumeration. The minimum inhibitory concentrations of HBD-1 and Pep B restricting growth of mycobacteria in vitro were 2μg/ml and 20μg/ml respectively. The intracellular mycobacterial load was reduced significantly by HBD-1 and Pep B at 1μg/ml and 5μg/ml respectively. Nile red positive bacterial population, high MPN/ low CFU count and tolerance to isoniazid, confirmed the formation of potassium deficienybaseddormancy model. HBD-1 (8μg/ml) showed 96% and 99% killing and Pep B (40μg/ml) lowered dormant bacillary load by 68.89% and 92.49% based on CFU and MPN enumeration respectively. Further, H&E stained aggregates of macrophages and lymphocytes, acid fast bacilli surrounded by cellular aggregates and rifampicin resistance, indicated the formation of human granuloma dormancy model. HBD-1 (8μg/ml) led to 81.3% reduction in CFU whereas its motif Pep B (40μg/ml) showed only 54.66% decrease in bacterial load inside granuloma. Thus, the present study indicated that HBD-1 and its motif are effective antimicrobial players against both actively growing and dormant M. tb. They should be further explored to tap their potential to design a powerful weapon for combating tuberculosis.

Keywords: antimicrobial peptides, dormant, human beta defensin 1, tuberculosis

Procedia PDF Downloads 243

Authors: Davide Cocchi, Andrea Zucchelli, Luca Raimondi, Maria Brugo Tommaso

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The increasing attention is given to the issues of environmental pollution and climate change is exponentially stimulating the development of electrically propelled vehicles powered by renewable energy, in particular, the solar one. Given the small amount of solar energy that can be stored and subsequently transformed into propulsive energy, it is necessary to develop vehicles with high mechanical, electrical and aerodynamic efficiencies along with reduced masses. The reduction of the masses is of fundamental relevance especially for the unsprung masses, that is the assembly of those elements that do not undergo a variation of their distance from the ground (wheel, suspension system, hub, upright, braking system). Therefore, the reduction of unsprung masses is fundamental in decreasing the rolling inertia and improving the drivability, comfort, and performance of the vehicle. This principle applies even more in solar propelled vehicles, equipped with an electric motor that is connected directly to the wheel hub. In this solution, the electric motor is integrated inside the wheel. Since the electric motor is part of the unsprung masses, the development of compact and lightweight solutions is of fundamental importance. The purpose of this research is the design development and optimization of a CFRP 16 wheel hub motor for solar propulsion vehicles that can carry up to four people. In addition to trying to maximize aspects of primary importance such as mass, strength, and stiffness, other innovative constructive aspects were explored. One of the main objectives has been to achieve a high geometric packing in order to ensure a reduced lateral dimension, without reducing the power exerted by the electric motor. In the final solution, it was possible to realize a wheel hub motor assembly completely comprised inside the rim width, for a total lateral overall dimension of less than 100 mm. This result was achieved by developing an innovative connection system between the wheel and the rotor with a double purpose: centering and transmission of the driving torque. This solution with appropriate interlocking noses allows the transfer of high torques and at the same time guarantees both the centering and the necessary stiffness of the transmission system. Moreover, to avoid delamination in critical areas, evaluated by means of FEM analysis using 3D Hashin damage criteria, electrospun nanofibrous mats have been interleaved between CFRP critical layers. In order to reduce rolling resistance, the rim has been designed to withstand high inflation pressure. Laboratory tests have been performed on the rim using the Digital Image Correlation technique (DIC). The wheel has been tested for fatigue bending according to E/ECE/324 R124e.

Keywords: composite laminate, delamination, DIC, lightweight vehicle, motor hub wheel, nanofiber

Procedia PDF Downloads 188

Authors: Narayana Bhat, Majda Khalil, Hamad Al-Mansour, Anitha Manuvel, Vimla Yeddu

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The aim of this study was to assess the antimicrobial and antioxidant potential and phytochemical composition of Peganum harmala L. For this purpose, powdered shoot, root, and seed samples were extracted in an accelerated solvent extractor (ASE) with methanol, ethanol, acetone, and dichloromethane. The residues were reconstituted in the above solvents and 10% dimethyl sulphoxide (DMSO). The antimicrobial activity of these extracts was tested against two bacterial (Escherichia coli E49 and Staphylococcus aureus CCUG 43507) and two fungi Candida albicans ATCC 24433, Candida glabrata ATCC 15545) strains using the well-diffusion method. The minimum inhibitory concentration (MIC) and growth pattern of these test strains were determined using microbroth dilution method, and the phospholipase assay was performed to detect tissue damage in the host cells. Results revealed that ethanolic, methanolic, and dichloromethane extracts of seeds exhibited significant antimicrobial activities against all tested strains, whereas the acetone extract of seeds was effective against E. coli only. Similarly, ethanolic and methanolic extracts of roots were effective against two bacterial strains only. One sixth of percent (0.6%) yield of methanol extract of seeds was found to be the MIC for Escherichia coli E49, Staphylococcus aureus CCUG 43507, and Candida glabrata ATCC 15545. Overall, seed extracts had greater antimicrobial activities compared to roots and shoot extracts. The original plant extract and MIC dilutions prevented phospholipase secretion in Staphylococcus aureus CCUG 43507 and Candida albicans ATCC 24433. The 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical scavenging assay revealed radical scavenging activities ranging from 71.80 ± 4.36% to 87.75 ± 1.70%. The main compound present in the root extract was 1-methyl-7-methoxy-beta-carboline (RT: 44.171), followed by norlapachol (3.62%), benzopyrazine (2.20%), palmitic acid (2.12%) and vasicinone (1.96%). In contrast, phenol,4-ethenyl-2-methoxy was in abundance in the methonolic extract of the shoot, whereas 1-methyl-7-methoxy-beta-carboline (79.59%), linoleic acid (9.05%), delta-tocopherol (5.02%), 9,12-octadecadienoic acid, methyl ester (2.65%), benzene, 1,1-1,2 ethanediyl bis 3,4dimethyl (1.15%), anthraquinone (0.58%), hexadecanoic acid, methyl ester (0.54%), palmitic acid (0.35%) and methyl stearate (0.18%) were present in the methanol extract of seeds. Major findings of this study, along with their relevance to developing effective, safe drugs, will be discussed in this presentation.

Keywords: medicinal plants, secondary metabolites, phytochemical screening, bioprospecting, radical scavenging

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Authors: Nguyen J. M., Lucas G., Ruan S., Digonnet H., Antonioli D.

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Introduction: Deep Learning (DL) is a very powerful tool for analyzing image data. But for tabular data, it cannot compete with machine learning methods like XGBoost. The research question becomes: can tabular data be transformed into images that can be analyzed by simple CNNs (Convolutional Neuron Networks)? Will DL be the absolute tool for data classification? All current solutions consist in repositioning the variables in a 2x2 matrix using their correlation proximity. In doing so, it obtains an image whose pixels are the variables. We implement a technology, DeepNIC, that offers the possibility of obtaining an image for each variable, which can be analyzed by simple CNNs. Material and method: The 'ROP' (Regression OPtimized) model is a binary and atypical decision tree whose nodes are managed by a new artificial neuron, the Neurop. By positioning an artificial neuron in each node of the decision trees, it is possible to make an adjustment on a theoretically infinite number of variables at each node. From this new decision tree whose nodes are artificial neurons, we created the concept of a 'Random Forest of Perfect Trees' (RFPT), which disobeys Breiman's concepts by assembling very large numbers of small trees with no classification errors. From the results of the RFPT, we developed a family of 10 statistical information criteria, Nguyen Information Criterion (NICs), which evaluates in 3 dimensions the predictive quality of a variable: Performance, Complexity and Multiplicity of solution. A NIC is a probability that can be transformed into a grey level. The value of a NIC depends essentially on 2 super parameters used in Neurops. By varying these 2 super parameters, we obtain a 2x2 matrix of probabilities for each NIC. We can combine these 10 NICs with the functions AND, OR, and XOR. The total number of combinations is greater than 100,000. In total, we obtain for each variable an image of at least 1166x1167 pixels. The intensity of the pixels is proportional to the probability of the associated NIC. The color depends on the associated NIC. This image actually contains considerable information about the ability of the variable to make the prediction of Y, depending on the presence or absence of other variables. A basic CNNs model was trained for supervised classification. Results: The first results are impressive. Using the GSE22513 public data (Omic data set of markers of Taxane Sensitivity in Breast Cancer), DEEPNic outperformed other statistical methods, including XGBoost. We still need to generalize the comparison on several databases. Conclusion: The ability to transform any tabular variable into an image offers the possibility of merging image and tabular information in the same format. This opens up great perspectives in the analysis of metadata.

Keywords: tabular data, CNNs, NICs, DeepNICs, random forest of perfect trees, classification

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Authors: Mohamed Bualhamam

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Due to the complex nature of tourism resources of the Northern part of the United Arab Emirates (UAE), the potential of Geographical Information Systems (GIS) and Remote Sensing (RS) in resolving these issues was used. The study was an attempt to use existing GIS data layers to identify sensitive natural environment and archaeological heritage resources that may be threatened by increased urban growth and give some specific recommendations to protect the area. By identifying sensitive natural environment and archaeological heritage resources, public agencies and citizens are in a better position to successfully protect important natural lands and direct growth away from environmentally sensitive areas. The paper concludes that applications of GIS and RS in study of urban growth impact in tourism resources are a strong and effective tool that can aid in tourism planning and decision-making. The study area is one of the fastest growing regions in the country. The increase in population along the region, as well as rapid growth of towns, has increased the threat to natural resources and archeological sites. Satellite remote sensing data have been proven useful in assessing the natural resources and in monitoring the changes. The study used GIS and RS to identify sensitive natural environment and archaeological heritage resources that may be threatened by increased urban growth. The result of GIS analyses shows that the Northern part of the UAE has variety for tourism resources, which can use for future tourism development. Rapid urban development in the form of small towns and different economic activities are showing in different places in the study area. The urban development extended out of old towns and have negative affected of sensitive tourism resources in some areas. Tourism resources for the Northern part of the UAE is a highly complex resources, and thus requires tools that aid in effective decision making to come to terms with the competing economic, social, and environmental demands of sustainable development. The UAE government should prepare a tourism databases and a GIS system, so that planners can be accessed for archaeological heritage information as part of development planning processes. Applications of GIS in urban planning, tourism and recreation planning illustrate that GIS is a strong and effective tool that can aid in tourism planning and decision- making. The power of GIS lies not only in the ability to visualize spatial relationships, but also beyond the space to a holistic view of the world with its many interconnected components and complex relationships. The worst of the damage could have been avoided by recognizing suitable limits and adhering to some simple environmental guidelines and standards will successfully develop tourism in sustainable manner. By identifying sensitive natural environment and archaeological heritage resources of the Northern part of the UAE, public agencies and private citizens are in a better position to successfully protect important natural lands and direct growth away from environmentally sensitive areas.

Keywords: GIS, natural environment, UAE, urban growth

Procedia PDF Downloads 236

Authors: Faidon Kyriakou, William Dempster, David Nash

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Abdominal Aortic Aneurysm (AAA) is a major life-threatening pathology for which modern approaches reduce the need for open surgery through the use of stenting. The success of stenting though is sometimes jeopardized by the final position of the stent graft inside the human artery which may result in migration, endoleaks or blood flow occlusion. Herein, a finite element (FE) model of the commercial medical device AnacondaTM (Vascutek, Terumo) has been developed and validated in order to create a numerical tool able to provide useful clinical insight before the surgical procedure takes place. The AnacondaTM device consists of a series of NiTi rings sewn onto woven polyester fabric, a structure that despite its column stiffness is flexible enough to be used in very tortuous geometries. For the purposes of this study, a FE model of the device was built in Abaqus® (version 6.13-2) with the combination of beam, shell and surface elements; the choice of these building blocks was made to keep the computational cost to a minimum. The validation of the numerical model was performed by comparing the deployed position of a full stent graft device inside a constructed AAA with a duplicate set-up in Abaqus®. Specifically, an AAA geometry was built in CAD software and included regions of both high and low tortuosity. Subsequently, the CAD model was 3D printed into a transparent aneurysm, and a stent was deployed in the lab following the steps of the clinical procedure. Images on the frontal and sagittal planes of the experiment allowed the comparison with the results of the numerical model. By overlapping the experimental and computational images, the mean and maximum distances between the rings of the two models were measured in the longitudinal, and the transverse direction and, a 5mm upper bound was set as a limit commonly used by clinicians when working with simulations. The two models showed very good agreement of their spatial positioning, especially in the less tortuous regions. As a result, and despite the inherent uncertainties of a surgical procedure, the FE model allows confidence that the final position of the stent graft, when deployed in vivo, can also be predicted with significant accuracy. Moreover, the numerical model run in just a few hours, an encouraging result for applications in the clinical routine. In conclusion, the efficient modelling of a complicated structure which combines thin scaffolding and fabric has been demonstrated to be feasible. Furthermore, the prediction capabilities of the location of each stent ring, as well as the global shape of the graft, has been shown. This can allow surgeons to better plan their procedures and medical device manufacturers to optimize their designs. The current model can further be used as a starting point for patient specific CFD analysis.

Keywords: AAA, efficiency, finite element analysis, stent deployment

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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: Hager Elsheikh

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Context: Pancreatitis is a condition characterized by inflammation in the pancreas, which can lead to serious complications if untreated. Both acute and chronic pancreatitis are associated with immune reactions and fibrosis, which further damage the pancreas. The type 2 immune response, primarily driven by alternative activated macrophages (AAMs), plays a significant role in the development of fibrosis. The IL-4/STAT6 pathway is a crucial signaling pathway for the activation of M2 macrophages. Pancreatic fibrosis is induced by dysregulated inflammatory responses and can result in the autodigestion and necrosis of pancreatic acinar cells. Research Aim: The aim of this study is to investigate the impact of STAT6, a crucial molecule in the IL-4/STAT6 pathway, on the severity and development of fibrosis during acute and chronic pancreatitis. The research also aims to understand the influence of the JAK/STAT6 signaling pathway on the balance between fibrosis and regeneration in the presence of different macrophage populations. Methodology: The research utilizes murine models of acute and chronic pancreatitis induced by cerulean injection. Animal models will be employed to study the effect of STAT6 knockout on disease severity and fibrosis. Isolation of acinar cells and cell culture techniques will be used to assess the impact of different macrophage populations on wound healing and regeneration. Various techniques such as PCR, histology, immunofluorescence, and transcriptomics will be employed to analyze the tissues and cells. Findings: The research aims to provide insights into the mechanisms underlying tissue fibrosis and wound healing during acute and chronic pancreatitis. By investigating the influence of the JAK/STAT6 signaling pathway and different macrophage populations, the study aims to understand their impact on tissue fibrosis, disease severity, and pancreatic regeneration. Theoretical Importance: This research contributes to our understanding of the role of specific signaling pathways, macrophage polarization, and the type 2 immune response in pancreatitis. It provides insights into the molecular mechanisms underlying tissue fibrosis and the potential for targeted therapies. Data Collection and Analysis Procedures: Data will be collected through the use of murine models, isolation and culture of acinar cells, and various experimental techniques such as PCR, histology, immunofluorescence, and transcriptomics. Data will be analyzed using appropriate statistical methods and techniques, and the findings will be interpreted in the context of the research objectives. Conclusion: By investigating the mechanisms of tissue fibrosis and wound healing during acute and chronic pancreatitis, this research aims to enhance our understanding of the disease progression and potential therapeutic targets. The findings have theoretical importance in expanding our knowledge of pancreatic fibrosis and the role of macrophage polarization in the context of the type 2 immune response.

Keywords: immunity in chronic diseases, pancreatitis, macrophages, immune response

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Authors: Vivek Hokam, Vishrut Landge

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An ideal maintenance program for an industrial road network is one that would maintain all sections at a sufficiently high level of functional and structural conditions. However, due to various constraints such as budget, manpower and equipment, it is not possible to carry out maintenance on all the needy industrial road sections within a given planning period. A rational and systematic priority scheme needs to be employed to select and schedule industrial road sections for maintenance. Priority analysis is a multi-criteria process that determines the best ranking list of sections for maintenance based on several factors. In priority setting, difficult decisions are required to be made for selection of sections for maintenance. It is more important to repair a section with poor functional conditions which includes uncomfortable ride etc. or poor structural conditions i.e. sections those are in danger of becoming structurally unsound. It would seem therefore that any rational priority setting approach must consider the relative importance of functional and structural condition of the section. The maintenance priority index and pavement performance models tend to focus mainly on the pavement condition, traffic criteria etc. There is a need to develop the model which is suitably used with respect to limited budget provisions for maintenance of pavement. Linear programming is one of the most popular and widely used quantitative techniques. A linear programming model provides an efficient method for determining an optimal decision chosen from a large number of possible decisions. The optimum decision is one that meets a specified objective of management, subject to various constraints and restrictions. The objective is mainly minimization of maintenance cost of roads in industrial area. In order to determine the objective function for analysis of distress model it is necessary to fix the realistic data into a formulation. Each type of repair is to be quantified in a number of stretches by considering 1000 m as one stretch. A stretch considered under study is having 3750 m length. The quantity has to be put into an objective function for maximizing the number of repairs in a stretch related to quantity. The distress observed in this stretch are potholes, surface cracks, rutting and ravelling. The distress data is measured manually by observing each distress level on a stretch of 1000 m. The maintenance and rehabilitation measured that are followed currently are based on subjective judgments. Hence, there is a need to adopt a scientific approach in order to effectively use the limited resources. It is also necessary to determine the pavement performance and deterioration prediction relationship with more accurate and economic benefits of road networks with respect to vehicle operating cost. The infrastructure of road network should have best results expected from available funds. In this paper objective function for distress model is determined by linear programming and deterioration model considering overloading is discussed.

Keywords: budget, maintenance, deterioration, priority

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Authors: C. Deangeli, P. Obentaku Obenebot, O. Omwanghe

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The study focuses on the analysis of wellbore instability in rock masses affected by weakness planes. The occurrence of failure in such a type of rocks can occur in the rock matrix and/ or along the weakness planes, in relation to the mud weight gradient. In this case the simple Kirsch solution coupled with a failure criterion cannot supply a suitable scenario for borehole instabilities. Two different numerical approaches have been used in order to investigate the onset of local failure at the wall of a borehole. For each type of approach the influence of the inclination of weakness planes has been investigates, by considering joint sets at 0°, 35° and 90° to the horizontal. The first set of models have been carried out with FLAC 2D (Fast Lagrangian Analysis of Continua) by considering the rock material as a continuous medium, with a Mohr Coulomb criterion for the rock matrix and using the ubiquitous joint model for accounting for the presence of the weakness planes. In this model yield may occur in either the solid or along the weak plane, or both, depending on the stress state, the orientation of the weak plane and the material properties of the solid and weak plane. The second set of models have been performed with PFC2D (Particle Flow code). This code is based on the Discrete Element Method and considers the rock material as an assembly of grains bonded by cement-like materials, and pore spaces. The presence of weakness planes is simulated by the degradation of the bonds between grains along given directions. In general the results of the two approaches are in agreement. However the discrete approach seems to capture more complex phenomena related to local failure in the form of grain detachment at wall of the borehole. In fact the presence of weakness planes in the discontinuous medium leads to local instability along the weak planes also in conditions not predicted from the continuous solution. In general slip failure locations and directions do not follow the conventional wellbore breakout direction but depend upon the internal friction angle and the orientation of the bedding planes. When weakness plane is at 0° and 90° the behaviour are similar to that of a continuous rock material, but borehole instability is more severe when weakness planes are inclined at an angle between 0° and 90° to the horizontal. In conclusion, the results of the numerical simulations show that the prediction of local failure at the wall of the wellbore cannot disregard the presence of weakness planes and consequently the higher mud weight required for stability for any specific inclination of the joints. Despite the discrete approach can simulate smaller areas because of the large number of particles required for the generation of the rock material, however it seems to investigate more correctly the occurrence of failure at the miscroscale and eventually the propagation of the failed zone to a large portion of rock around the wellbore.

Keywords: continuous- discontinuous, numerical modelling, weakness planes wellbore, FLAC 2D

Procedia PDF Downloads 477