Search results for: cell detection

Authors: Nadarajah I. Ramesh

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Much of the research on stochastic point process models for rainfall has focused on Poisson cluster models constructed from either the Neyman-Scott or Bartlett-Lewis processes. The doubly stochastic Poisson process provides a rich class of point process models, especially for fine-scale rainfall modelling. This paper provides an account of recent development on this topic and presents the results based on some of the fine-scale rainfall models constructed from this class of stochastic point processes. Amongst the literature on stochastic models for rainfall, greater emphasis has been placed on modelling rainfall data recorded at hourly or daily aggregation levels. Stochastic models for sub-hourly rainfall are equally important, as there is a need to reproduce rainfall time series at fine temporal resolutions in some hydrological applications. For example, the study of climate change impacts on hydrology and water management initiatives requires the availability of data at fine temporal resolutions. One approach to generating such rainfall data relies on the combination of an hourly stochastic rainfall simulator, together with a disaggregator making use of downscaling techniques. Recent work on this topic adopted a different approach by developing specialist stochastic point process models for fine-scale rainfall aimed at generating synthetic precipitation time series directly from the proposed stochastic model. One strand of this approach focused on developing a class of doubly stochastic Poisson process (DSPP) models for fine-scale rainfall to analyse data collected in the form of rainfall bucket tip time series. In this context, the arrival pattern of rain gauge bucket tip times N(t) is viewed as a DSPP whose rate of occurrence varies according to an unobserved finite state irreducible Markov process X(t). Since the likelihood function of this process can be obtained, by conditioning on the underlying Markov process X(t), the models were fitted with maximum likelihood methods. The proposed models were applied directly to the raw data collected by tipping-bucket rain gauges, thus avoiding the need to convert tip-times to rainfall depths prior to fitting the models. One advantage of this approach was that the use of maximum likelihood methods enables a more straightforward estimation of parameter uncertainty and comparison of sub-models of interest. Another strand of this approach employed the DSPP model for the arrivals of rain cells and attached a pulse or a cluster of pulses to each rain cell. Different mechanisms for the pattern of the pulse process were used to construct variants of this model. We present the results of these models when they were fitted to hourly and sub-hourly rainfall data. The results of our analysis suggest that the proposed class of stochastic models is capable of reproducing the fine-scale structure of the rainfall process, and hence provides a useful tool in hydrological modelling.

Keywords: fine-scale rainfall, maximum likelihood, point process, stochastic model

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Authors: Katarina Pogacnik, Ursa Zakrajsek, Nejc Sirk, Ziga Lampret

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Due to an increase in living standards along with global population growth and a trend of urbanization, municipalities and regions are faced with an ever rising energy demand. A challenge has arisen for cities around the world to modify the energy supply chain in order to reduce its consumption and CO₂ emissions. The aim of our work is the development of a computational-analytical platform for dynamic support in decision-making and the determination of economic and technical indicators of energy efficiency in a smart city, named Energy Atlas. Similar products in this field focuse on a narrower approach, whereas in order to achieve its aim, this platform encompasses a wider spectrum of beneficial and important information for energy planning on a local or regional scale. GIS based interactive maps provide an extensive database on the potential, use and supply of energy and renewable energy sources along with climate, transport and spatial data of the selected municipality. Beneficiaries of Energy atlas are local communities, companies, investors, contractors as well as residents. The Energy Atlas platform consists of three modules named E-Planning, E-Indicators and E-Cooperation. The E-Planning module is a comprehensive data service, which represents a support towards optimal decision-making and offers a sum of solutions and feasibility of measures and their effects in the area of efficient use of energy and renewable energy sources. The E-Indicators module identifies, collects and develops optimal data and key performance indicators and develops an analytical application service for dynamic support in managing a smart city in regards to energy use and sustainable environment. In order to support cooperation and direct involvement of citizens of the smart city, the E-cooperation is developed with the purpose of integrating the interdisciplinary and sociological aspects of energy end-users. Interaction of all the above-described modules contributes to regional development because it enables for a precise assessment of the current situation, strategic planning, detection of potential future difficulties and also the possibility of public involvement in decision-making. From the implementation of the technology in Slovenian municipalities of Ljubljana, Piran, and Novo mesto, there is evidence to suggest that the set goals are to be achieved to a great extent. Such thorough urban energy planning tool is viewed as an important piece of the puzzle towards achieving a low-carbon society, circular economy and therefore, sustainable society.

Keywords: circular economy, energy atlas, energy management, energy planning, low-carbon society

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Authors: Joanna Gerszon, Aleksandra Rodacka

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In the pathogenesis of neurodegenerative diseases such as Alzheimer's disease and Parkinson's disease, protein and peptide aggregation processes play a vital role in contributing to the formation of intracellular and extracellular protein deposits. One of the major components of these deposits is the oxidatively modified glyceraldehyde-3-phosphate dehydrogenase (GAPDH). Therefore, the purpose of this research was to answer the question whether piceatannol, a stilbene derivative, counteracts and/or slows down oxidative stress-induced GAPDH aggregation. The study also aimed to determine if this natural occurring compound prevents unfavorable nuclear translocation of GAPDH in hippocampal cells. The isothermal titration calorimetry (ITC) analysis indicated that one molecule of GAPDH can bind up to 8 molecules of piceatannol (7.3 ± 0.9). As a consequence of piceatannol binding to the enzyme, the loss of activity was observed. Parallel with GAPDH inactivation the changes in zeta potential, and loss of free thiol groups were noted. Nevertheless, the ligand-protein binding does not influence the secondary structure of the GAPDH. Precise molecular docking analysis of the interactions inside the active center allowed to presume that these effects are due to piceatannol ability to assemble a covalent binding with nucleophilic cysteine residue (Cys149) which is directly involved in the catalytic reaction. Molecular docking also showed that simultaneously 11 molecules of ligand can be bound to dehydrogenase. Taking into consideration obtained data, the influence of piceatannol on level of GAPDH aggregation induced by excessive oxidative stress was examined. The applied methods (thioflavin-T binding-dependent fluorescence as well as microscopy methods - transmission electron microscopy, Congo Red staining) revealed that piceatannol significantly diminishes level of GAPDH aggregation. Finally, studies involving cellular model (Western blot analyses of nuclear and cytosolic fractions and confocal microscopy) indicated that piceatannol-GAPDH binding prevents GAPDH from nuclear translocation induced by excessive oxidative stress in hippocampal cells. In consequence, it counteracts cell apoptosis. These studies demonstrate that by binding with GAPDH, piceatannol blocks cysteine residue and counteracts its oxidative modifications, that induce oligomerization and GAPDH aggregation as well as it prevents hippocampal cells from apoptosis by retaining GAPDH in the cytoplasm. All these findings provide a new insight into the role of piceatannol interaction with GAPDH and present a potential therapeutic strategy for some neurological disorders related to GAPDH aggregation. This work was supported by the by National Science Centre, Poland (grant number 2017/25/N/NZ1/02849).

Keywords: glyceraldehyde-3-phosphate dehydrogenase, neurodegenerative disease, neuroprotection, piceatannol, protein aggregation

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Authors: N. Demertzis, J. L. Bowen

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Sepsis is a complex and rapidly evolving condition, resulting from uncontrolled prolonged activation of host immune system due to pathogenic insult. The aim of this study is the development of a multiplex electrochemical sensing platform, capable of detecting both pathogen associated and host immune markers to enable the rapid and definitive diagnosis of sepsis. A combination of aptamers and molecular imprinting approaches have been employed to generate sensing systems for lipopolysaccharide (LPS), c-reactive protein (CRP) and procalcitonin (PCT). Gold working electrodes were mechanically polished and electrochemically cleaned with 0.1 M sulphuric acid using cyclic voltammetry (CV). Following activation, a self-assembled monolayer (SAM) was generated, by incubating the electrodes with a thiolated anti-LPS aptamer / dithiodibutiric acid (DTBA) mixture (1:20). 3-aminophenylboronic acid (3-APBA) in combination with the anti-LPS aptamer was used for the development of the hybrid molecularly imprinted sensor (apta-MIP). Aptasensors, targeting PCT and CRP were also fabricated, following the same approach as in the case of LPS, with mercaptohexanol (MCH) replacing DTBA. In the case of the CRP aptasensor, the SAM was formed following incubation of a 1:1 aptamer: MCH mixture. However, in the case of PCT, the SAM was formed with the aptamer itself, with subsequent backfilling with 1 μM MCH. The binding performance of all systems has been evaluated using electrochemical impedance spectroscopy. The apta-MIP’s polymer thickness is controlled by varying the number of electropolymerisation cycles. In the ideal number of polymerisation cycles, the polymer must cover the electrode surface and create a binding pocket around LPS and its aptamer binding site. Less polymerisation cycles will create a hybrid system which resembles an aptasensor, while more cycles will be able to cover the complex and demonstrate a bulk polymer-like behaviour. Both aptasensor and apta-MIP were challenged with LPS and compared to conventional imprinted (absence of aptamer from the binding site, polymer formed in presence of LPS) and non-imprinted polymers (NIPS, absence of LPS whilst hybrid polymer is formed). A stable LPS aptasensor, capable of detecting down to 5 pg/ml of LPS was generated. The apparent Kd of the system was estimated at 17 pM, with a Bmax of approximately 50 pM. The aptasensor demonstrated high specificity to LPS. The apta-MIP demonstrated superior recognition properties with a limit of detection of 1 fg/ml and a Bmax of 100 pg/ml. The CRP and PCT aptasensors were both able to detect down to 5 pg/ml. Whilst full binding performance is currently being evaluated, there is none of the sensors demonstrate cross-reactivity towards LPS, CRP or PCT. In conclusion, stable aptasensors capable of detecting LPS, PCT and CRP at low concentrations have been generated. The realisation of a multiplex panel such as described herein, will effectively contribute to the rapid, personalised diagnosis of sepsis.

Keywords: aptamer, electrochemical impedance spectroscopy, molecularly imprinted polymers, sepsis

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Authors: Ching Shya Lee, Mohamed Kheireddine Aroua, Wan Mohd Ashri Wan Daud, Patrick Cognet, Yolande Peres, Mohammed Ajeel

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In recent years, with the decreasing supply of fossil fuel, renewable energy has received a significant demand. Biodiesel which is well known as vegetable oil based fatty acid methyl ester is an alternative fuel for diesel. It can be produced from transesterification of vegetable oils, such as palm oil, sunflower oil, rapeseed oil, etc., with methanol. During the transesterification process, crude glycerol is formed as a by-product, resulting in 10% wt of the total biodiesel production. To date, due to the fast growing of biodiesel production in worldwide, the crude glycerol supply has also increased rapidly and resulted in a significant price drop for glycerol. Therefore, extensive research has been developed to use glycerol as feedstock to produce various added-value chemicals, such as tartronic acid, mesoxalic acid, glycolic acid, glyceric acid, propanediol, acrolein etc. The industrial processes that usually involved are selective oxidation, biofermentation, esterification, and hydrolysis. However, the conversion of glycerol into added-value compounds by electrochemical approach is rarely discussed. Currently, the approach is mainly focused on the electro-oxidation study of glycerol under potentiostatic mode for cogenerating energy with other chemicals. The electro-organic synthesis study from glycerol under galvanostatic mode is seldom reviewed. In this study, the glycerol was converted into various added-value compounds by electrochemical method under galvanostatic mode. This work aimed to study the possible compounds produced from glycerol by electrochemical technique in a one-pot electrolysis cell. The electro-organic synthesis study from glycerol was carried out in a single compartment reactor for 8 hours, over the platinum cathode and anode electrodes under acidic condition. Various parameters such as electric current (1.0 A to 3.0 A) and reaction temperature (27 °C to 80 °C) were evaluated. The products obtained were characterized by using gas chromatography-mass spectroscopy equipped with an aqueous-stable polyethylene glycol stationary phase column. Under the optimized reaction condition, the glycerol conversion achieved as high as 95%. The glycerol was successfully converted into various added-value chemicals such as ethylene glycol, glycolic acid, glyceric acid, acetaldehyde, formic acid, and glyceraldehyde; given the yield of 1%, 45%, 27%, 4%, 0.7% and 5%, respectively. Based on the products obtained from this study, the reaction mechanism of this process is proposed. In conclusion, this study has successfully converted glycerol into a wide variety of added-value compounds. These chemicals are found to have high market value; they can be used in the pharmaceutical, food and cosmetic industries. This study effectively opens a new approach for the electrochemical conversion of glycerol. For further enhancement on the product selectivity, electrode material is an important parameter to be considered.

Keywords: biodiesel, glycerol, electrochemical conversion, galvanostatic mode

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Authors: S. A. Bhat, Ahmad Arif, Muneeb U. Rehman, Manzoor R Mir, S. Bilal, Ishraq Hussain, H. M Khan, S. Shanaz, M. I Mir, Sabhiya Majid

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Background: Geologically Climatic conditions of the state range from sub-tropical (Jammu), temperate (Kashmir) to cold artic (Ladakh) zones, which exerts significant influence on its agro-climatic conditions. Gastrointestinal parasitism is a major problem in sheep production worldwide. Materials and Methods: The present study was to evaluate the resistance status of sheep breeds reared in Kashmir Valley for natural resistance against Haemonchus contortus by natural pasture challenge infection. Ten microsatellite markers were used in the study for evaluation of association of Ovar-MHC with parasitic resistance in association with biochemical and parasitological parameters. Following deworming, 500 animals were subjected to selected contaminated pastures in a vicinity of the livestock farms of SKUAST-K and Sheep Husbandry Kashmir. For each animal about 10-15 ml blood was collected aseptically for molecular and biochemical analysis. Weekly fecal samples (3g) were taken, directly from the rectum of all experimental animals and examined for Fecal egg count (FEC) with modified McMaster technique. Packed cell volume (PCV) was determined within 2-5 h of blood collection, all the biochemical parameters were determined in serum by semi automated analyzer. DNA was extracted from all the blood samples with phenol-chloroform method. Microsatellite analysis was done by denaturing sequencing gel electrophoresis Results: Overall sheep from Bakerwal breed followed by Corriediale breed performed relatively better in the trial; however difference between breeds remained low. Both significant (P<0.05) and non-significant differences with respect to resistance against haemonchosis were noted at different intervals in all the parameters.. All the animals were typed for the microsatellites INRA132, OarCP73, DRB1 (U0022), OLA-DQA2, BM1818, TFAP2A, HH56, BM1815, IL-3 and BM-1258. An association study including the effect of FEC, PCV, TSP, SA, LW, and the number of alleles within each marker was done. All microsatellite markers showed degree of heterozygosity of 0.72, 0.72, 0.75, 0.62, 0.84, 0.69, 0.66, 0.65, 0.73 and 0.68 respectively. Significant association between alleles and the parameters measured were only found for the OarCP73, OLA-DQA2 and BM1815 microsatellite marker. Standard alleles of the above markers showed significant effect on the TP, SA and body weight. The three sheep breeds included in the study responded differently to the nematode infection, which may be attributed to their differences in their natural resistance against nematodes. Conclusion: Our data confirms that some markers (OarCP73, OLA-DQA2 and BM1815) within Ovar-MHC are associated with phenotypic parameters of resistance and suggest superiority of Bakerwal sheep breed in natural resistance against Haemonchus contortus.

Keywords: Ovar-Mhc, ovine leukocyte antigen (OLA), sheep, parasitic resistance, Haemonchus contortus, phenotypic & genotypic markers

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Authors: Mohammad H. Taheri, David J. Brown, Nasser Sherkat

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Engagement is one of the most important factors in determining successful outcomes and deep learning in students. Existing approaches to detect student engagement involve periodic human observations that are subject to inter-rater reliability. Our solution uses real-time multimodal multisensor data labeled by objective performance outcomes to infer the engagement of students. The study involves four students with a combined diagnosis of cerebral palsy and a learning disability who took part in a 3-month trial over 59 sessions. Multimodal multisensor data were collected while they participated in a continuous performance test. Eye gaze, electroencephalogram, body pose, and interaction data were used to create a model of student engagement through objective labeling from the continuous performance test outcomes. In order to achieve this, a type of continuous performance test is introduced, the Seek-X type. Nine features were extracted including high-level handpicked compound features. Using leave-one-out cross-validation, a series of different machine learning approaches were evaluated. Overall, the random forest classification approach achieved the best classification results. Using random forest, 93.3% classification for engagement and 42.9% accuracy for disengagement were achieved. We compared these results to outcomes from different models: AdaBoost, decision tree, k-Nearest Neighbor, naïve Bayes, neural network, and support vector machine. We showed that using a multisensor approach achieved higher accuracy than using features from any reduced set of sensors. We found that using high-level handpicked features can improve the classification accuracy in every sensor mode. Our approach is robust to both sensor fallout and occlusions. The single most important sensor feature to the classification of engagement and distraction was shown to be eye gaze. It has been shown that we can accurately predict the level of engagement of students with learning disabilities in a real-time approach that is not subject to inter-rater reliability, human observation or reliant on a single mode of sensor input. This will help teachers design interventions for a heterogeneous group of students, where teachers cannot possibly attend to each of their individual needs. Our approach can be used to identify those with the greatest learning challenges so that all students are supported to reach their full potential.

Keywords: affective computing in education, affect detection, continuous performance test, engagement, flow, HCI, interaction, learning disabilities, machine learning, multimodal, multisensor, physiological sensors, student engagement

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Authors: Ayten Ekin Meşe, Selahattin Şentürk, Melike Duvanoğlu

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Petroleum refineries are a highly complex process industry with continuous production and high operating costs. Physical separation of crude oil starts with the crude oil distillation unit, continues with various conversion and purification units, and passes through many stages until obtaining the final product. To meet the desired product specification, process parameters are strictly followed. To be able to ensure the quality of distillates, routine analyses are performed in quality control laboratories based on appropriate international standards such as American Society for Testing and Materials (ASTM) standard methods and European Standard (EN) methods. The cut point of distillates in the crude distillation unit is very crucial for the efficiency of the upcoming processes. In order to maximize the process efficiency, the determination of the quality of distillates should be as fast as possible, reliable, and cost-effective. In this sense, an alternative study was carried out on the crude oil distillation unit that serves the entire refinery process. In this work, studies were conducted with three different crude oil distillates which are Light Straight Run Naphtha (LSRN), Heavy Straight Run Naphtha (HSRN), and Kerosene. These products are named after separation by the number of carbons it contains. LSRN consists of five to six carbon-containing hydrocarbons, HSRN consist of six to ten, and kerosene consists of sixteen to twenty-two carbon-containing hydrocarbons. Physical properties of three different crude distillation unit products (LSRN, HSRN, and Kerosene) were determined using Near-Infrared Spectroscopy with multivariate calibration. The absorbance spectra of the petroleum samples were obtained in the range from 10000 cm⁻¹ to 4000 cm⁻¹, employing a quartz transmittance flow through cell with a 2 mm light path and a resolution of 2 cm⁻¹. A total of 400 samples were collected for each petroleum sample for almost four years. Several different crude oil grades were processed during sample collection times. Extended Multiplicative Signal Correction (EMSC) and Savitzky-Golay (SG) preprocessing techniques were applied to FT-NIR spectra of samples to eliminate baseline shifts and suppress unwanted variation. Two different multivariate calibration approaches (Partial Least Squares Regression, PLS and Genetic Inverse Least Squares, GILS) and an ensemble model were applied to preprocessed FT-NIR spectra. Predictive performance of each multivariate calibration technique and preprocessing techniques were compared, and the best models were chosen according to the reproducibility of ASTM reference methods. This work demonstrates the developed models can be used for routine analysis instead of conventional analytical methods with over 90% accuracy.

Keywords: crude distillation unit, multivariate calibration, near infrared spectroscopy, data preprocessing, refinery

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Authors: Seyed Mehdi Seyed Alizadeh, Christoph Arns, Shane Latham

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Geomechanical characterization of rocks in detail and its possible implications on flow properties is an important aspect of reservoir characterization workflow. In order to gain more understanding of the microstructure evolution of reservoir rocks under stress a series of axisymmetric triaxial tests were performed on two different analogue rock samples. In-situ compression tests were coupled with high resolution micro-Computed Tomography to elucidate the changes in the pore/grain network of the rocks under pressurized conditions. Two outcrop sandstones were chosen in the current study representing a various cementation status of well-consolidated and weakly-consolidated granular system respectively. High resolution images were acquired while the rocks deformed in a purpose-built compression cell. A detailed analysis of the 3D images in each series of step-wise compression tests (up to the failure point) was conducted which includes the registration of the deformed specimen images with the reference pristine dry rock image. Digital Image Correlation (DIC) technique based on the intensity of the registered 3D subsets and particle tracking are utilized to map the displacement fields in each sample. The results suggest the complex architecture of the localized shear zone in well-cemented Bentheimer sandstone whereas for the weakly-consolidated Castlegate sandstone no discernible shear band could be observed even after macroscopic failure. Post-mortem imaging a sister plug from the friable rock upon undergoing continuous compression reveals signs of a shear band pattern. This suggests that for friable sandstones at small scales loading mode may affect the pattern of deformation. Prior to mechanical failure, the continuum digital image correlation approach can reasonably capture the kinematics of deformation. As failure occurs, however, discrete image correlation (i.e. particle tracking) reveals superiority in both tracking the grains as well as quantifying their kinematics (in terms of translations/rotations) with respect to any stage of compaction. An attempt was made to quantify the displacement field in compression using continuum Digital Image Correlation which is based on the reference and secondary image intensity correlation. Such approach has only been previously applied to unconsolidated granular systems under pressure. We are applying this technique to sandstones with various degrees of consolidation. Such element of novelty will set the results of this study apart from previous attempts to characterize the deformation pattern in consolidated sands.

Keywords: deformation mechanism, displacement field, shear behavior, triaxial compression, X-ray micro-CT

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Authors: Tomasz Borowski, Dawid Sołoducha, Agata Markowska-Szczupak, Aneta Wesołowska, Marian Kordas, Rafał Rakoczy

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Essential oils (EOs) are fragrant volatile oils obtained from plants. These are used for cooking (for flavor and aroma), cleaning, beauty (e.g., rosemary essential oil is used to promote hair growth), health (e.g. thyme essential oil cures arthritis, normalizes blood pressure, reduces stress on the heart, cures chest infection and cough) and in the food industry as preservatives and antioxidants. Rosemary and thyme essential oils are considered the most eminent herbs based on their history and medicinal properties. They possess a wide range of activity against different types of bacteria and fungi compared with the other oils in both in vitro and in vivo studies. However, traditional uses of EOs are limited due to rosemary and thyme oils in high concentrations can be toxic. In light of the accessible data, the following hypothesis was put forward: Low frequency rotating magnetic field (RMF) increases the antimicrobial potential of EOs. The aim of this work was to investigate the antimicrobial activity of commercial Salvia Rosmarinus L. and Thymus vulgaris L. essential oil from Polish company Avicenna-Oil under Rotating Magnetic Field (RMF) at f = 25 Hz. The self-constructed reactor (MAP) was applied for this study. The chemical composition of oils was determined by gas chromatography coupled with mass spectrometry (GC-MS). Model bacteria Escherichia coli K12 (ATCC 25922) was used. Minimum inhibitory concentrations (MIC) against E. coli were determined for the essential oils. Tested oils in very small concentrations were prepared (from 1 to 3 drops of essential oils per 3 mL working suspensions). From the results of disc diffusion assay and MIC tests, it can be concluded that thyme oil had the highest antibacterial activity against E. coli. Moreover, the study indicates the exposition to the RMF, as compared to the unexposed controls causing an increase in the efficacy of antibacterial properties of tested oils. The extended radiation exposure to RMF at the frequency f= 25 Hz beyond 160 minutes resulted in a significant increase in antibacterial potential against E. coli. Bacteria were killed within 40 minutes in thyme oil in lower tested concentration (1 drop of essential oils per 3 mL working suspension). Rapid decrease (>3 log) of bacteria number was observed with rosemary oil within 100 minutes (in concentration 3 drops of essential oils per 3 mL working suspension). Thus, a method for improving the antimicrobial performance of essential oil in low concentrations was developed. However, it still remains to be investigated how bacteria get killed by the EOs treated by an electromagnetic field. The possible mechanisms relies on alteration in the permeability of ionic channels in ionic channels in the bacterial cell walls that transport in the cells was proposed. For further studies, it is proposed to examine other types of essential oils and other antibiotic-resistant bacteria (ARB), which are causing a serious concern throughout the world.

Keywords: rotating magnetic field, rosemary, thyme, essential oils, Escherichia coli

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Authors: Olena Kavats, Dmitry Khramov, Kateryna Sergieieva, Vladimir Vasyliev, Iurii Kavats

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Geoinformation technologies of space agromonitoring are a means of operative decision making support in the tasks of managing the agricultural sector of the economy. Existing technologies use satellite images in the optical range of electromagnetic spectrum. Time series of optical images often contain gaps due to the presence of clouds and haze. A geoinformation technology is created. It allows to fill gaps in time series of optical images (Sentinel-2, Landsat-8, PROBA-V, MODIS) with radar survey data (Sentinel-1) and use information about agrometeorological conditions of the growing season for individual monitoring years. The technology allows to perform crop classification and mapping for spring-summer (winter and spring crops) and autumn-winter (winter crops) periods of vegetation, monitoring the dynamics of crop state seasonal changes, crop yield forecasting. Crop classification is based on supervised classification algorithms, takes into account the peculiarities of crop growth at different vegetation stages (dates of sowing, emergence, active vegetation, and harvesting) and agriculture land state characteristics (row spacing, seedling density, etc.). A catalog of samples of the main agricultural crops (Ukraine) is created and crop spectral signatures are calculated with the preliminary removal of row spacing, cloud cover, and cloud shadows in order to construct time series of crop growth characteristics. The obtained data is used in grain crop growth tracking and in timely detection of growth trends deviations from reference samples of a given crop for a selected date. Statistical models of crop yield forecast are created in the forms of linear and nonlinear interconnections between crop yield indicators and crop state characteristics (temperature, precipitation, vegetation indices, etc.). Predicted values of grain crop yield are evaluated with an accuracy up to 95%. The developed technology was used for agricultural areas monitoring in a number of Great Britain and Ukraine regions using EOS Crop Monitoring Platform (https://crop-monitoring.eos.com). The obtained results allow to conclude that joint use of Sentinel-1 and Sentinel-2 images improve separation of winter crops (rapeseed, wheat, barley) in the early stages of vegetation (October-December). It allows to separate successfully the soybean, corn, and sunflower sowing areas that are quite similar in their spectral characteristics.

Keywords: geoinformation technology, crop classification, crop yield prediction, agricultural monitoring, EOS Crop Monitoring Platform

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Authors: Jeanne Leblond, Warren Viricel, Amira Mbarek

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Although several products have reached the market, gene therapeutics are still in their first stages and require optimization. It is possible to improve their lacking efficiency by the use of carefully engineered vectors, able to carry the genetic material through each of the biological barriers they need to cross. In particular, getting inside the cell is a major challenge, because these hydrophilic nucleic acids have to cross the lipid-rich plasmatic and/or endosomal membrane, before being degraded into lysosomes. It takes less than one hour for newly endocytosed liposomes to reach highly acidic lysosomes, meaning that the degradation of the carried gene occurs rapidly, thus limiting the transfection efficiency. We propose to use a new pH-sensitive lipid able to change its conformation upon protonation at endosomal pH values, leading to the disruption of the lipidic bilayer and thus to the fast release of the nucleic acids into the cytosol. It is expected that this new pH-sensitive mechanism promote endosomal escape of the gene, thereby its transfection efficiency. The main challenge of this work was to design a preparation presenting fast-responding lipidic bilayer destabilization properties at endosomal pH 5 while remaining stable at blood pH value and during storage. A series of pH-sensitive lipids able to perform a conformational switch upon acidification were designed and synthesized. Liposomes containing these switchable lipids, as well as co-lipids were prepared and characterized. The liposomes were stable at 4°C and pH 7.4 for several months. Incubation with siRNA led to the full entrapment of nucleic acids as soon as the positive/negative charge ratio was superior to 2. The best liposomal formulation demonstrated a silencing efficiency up to 10% on HeLa cells, very similar to a commercial agent, with a lowest toxicity than the commercial agent. Using flow cytometry and microscopy assays, we demonstrated that drop of pH was required for the transfection efficiency, since bafilomycin blocked the transfection efficiency. Additional evidence was brought by the synthesis of a negative control lipid, which was unable to switch its conformation, and consequently exhibited no transfection ability. Mechanistic studies revealed that the uptake was mediated through endocytosis, by clathrin and caveolae pathways, as reported for previous lipid nanoparticle systems. This potent system was used for the treatment of hypercholesterolemia. The switchable lipids were able to knockdown PCSK9 expression on human hepatocytes (Huh-7). Its efficiency is currently evaluated on in vivo mice model of PCSK9 KO mice. In summary, we designed and optimized a new cationic pH-sensitive lipid for gene delivery. Its transfection efficiency is similar to the best available commercial agent, without the usually associated toxicity. The promising results lead to its use for the treatment of hypercholesterolemia on a mice model. Anticancer applications and pulmonary chronic disease are also currently investigated.

Keywords: liposomes, siRNA, pH-sensitive, molecular switch

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Authors: Ran Goldblatt, Nicholas Jones, Jennifer Mannix, Brad Bottoms

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Accurate, complete, and up-to-date geospatial information is the foundation of successful disaster management. When the 2010 Haiti Earthquake struck, accurate and timely information on the distribution of critical infrastructure was essential for the disaster response community for effective search and rescue operations. Existing geospatial datasets such as Google Maps did not have comprehensive coverage of these features. In the days following the earthquake, many organizations released high-resolution satellite imagery, catalyzing a worldwide effort to map Haiti and support the recovery operations. Of these organizations, OpenStreetMap (OSM), a collaborative project to create a free editable map of the world, used the imagery to support volunteers to digitize roads, buildings, and other features, creating the most detailed map of Haiti in existence in just a few weeks. However, large portions of the island are still not fully covered by OSM. There is an increasing need for a tool to automatically identify which areas in Haiti, as well as in other countries vulnerable to disasters, that are not fully mapped. The objective of this project is to leverage different types of remote sensing measurements, together with machine learning approaches, in order to identify geographical areas where OSM coverage of building footprints is incomplete. Several remote sensing measures and derived products were assessed as potential predictors of OSM building footprints coverage, including: intensity of light emitted at night (based on VIIRS measurements), spectral indices derived from Sentinel-2 satellite (normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), soil-adjusted vegetation index (SAVI), urban index (UI)), surface texture (based on Sentinel-1 SAR measurements)), elevation and slope. Additional remote sensing derived products, such as Hansen Global Forest Change, DLR`s Global Urban Footprint (GUF), and World Settlement Footprint (WSF), were also evaluated as predictors, as well as OSM street and road network (including junctions). Using a supervised classification with a random forest classifier resulted in the prediction of 89% of the variation of OSM building footprint area in a given cell. These predictions allowed for the identification of cells that are predicted to be covered but are actually not mapped yet. With these results, this methodology could be adapted to any location to assist with preparing for future disastrous events and assure that essential geospatial information is available to support the response and recovery efforts during and following major disasters.

Keywords: disaster management, Haiti, machine learning, OpenStreetMap, remote sensing

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Authors: Ali H. Daraji, Jack M. Hale, Ye Jianqiao

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With the extensive use of high specific strength structures to optimise the loading capacity and material cost in aerospace and most engineering applications, much effort has been expended to develop intelligent structures for active vibration reduction and structural health monitoring. These structures are highly flexible, inherently low internal damping and associated with large vibration and long decay time. The modification of such structures by adding lightweight piezoelectric sensors and actuators at efficient locations integrated with an optimal control scheme is considered an effective solution for structural vibration monitoring and controlling. The size and location of sensor and actuator are important research topics to investigate their effects on the level of vibration detection and reduction and the amount of energy provided by a controller. Several methodologies have been presented to determine the optimal location of a limited number of sensors and actuators for small-scale structures. However, these studies have tackled this problem directly, measuring the fitness function based on eigenvalues and eigenvectors achieved with numerous combinations of sensor/actuator pair locations and converging on an optimal set using heuristic optimisation techniques such as the genetic algorithms. This is computationally expensive for small- and large-scale structures subject to optimise a number of s/a pairs to suppress multiple vibration modes. This paper proposes an efficient method to determine optimal locations for a limited number of sensor/actuator pairs for active vibration reduction of a flexible structure based on finite element method and Hamilton’s principle. The current work takes the simplified approach of modelling a structure with sensors at all locations, subjecting it to an external force to excite the various modes of interest and noting the locations of sensors giving the largest average percentage sensors effectiveness measured by dividing all sensor output voltage over the maximum for each mode. The methodology was implemented for a cantilever plate under external force excitation to find the optimal distribution of six sensor/actuator pairs to suppress the first six modes of vibration. It is shown that the results of the optimal sensor locations give good agreement with published optimal locations, but with very much reduced computational effort and higher effectiveness. Furthermore, it is shown that collocated sensor/actuator pairs placed in these locations give very effective active vibration reduction using optimal linear quadratic control scheme.

Keywords: optimisation, plate, sensor effectiveness, vibration control

Procedia PDF Downloads 231

Authors: Sergey N. Ermoliev, Margarita A. Belousova, Aida D. Goncharenko

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Application of the diagnostic complex of highly informative functional methods (electromyography, reodentography, laser Doppler flowmetry, reoperiodontography, vital computer capillaroscopy, optical tissue oximetry, laser fluorescence diagnosis) allows to perform a multifactorial analysis of the dental status and to prescribe complex etiopathogenetic treatment. Introduction. It is necessary to create a complex of innovative highly informative and safe functional diagnostic methods for improvement of the quality of patient treatment by the early detection of stomatologic diseases. The purpose of the present study was to investigate the etiology and pathogenesis of functional disorders identified in the pathology of hard tissue, dental pulp, periodontal, oral mucosa and chewing function, and the creation of new approaches to the diagnosis of dental diseases. Material and methods. 172 patients were examined. Density of hard tissues of the teeth and jaw bone was studied by intraoral ultrasonic densitometry (USD). Electromyographic activity of masticatory muscles was assessed by electromyography (EMG). Functional state of dental pulp vessels assessed by reodentography (RDG) and laser Doppler flowmetry (LDF). Reoperiodontography method (RPG) studied regional blood flow in the periodontal tissues. Microcirculatory vascular periodontal studied by vital computer capillaroscopy (VCC) and laser Doppler flowmetry (LDF). The metabolic level of the mucous membrane was determined by optical tissue oximetry (OTO) and laser fluorescence diagnosis (LFD). Results and discussion. The results obtained revealed changes in mineral density of hard tissues of the teeth and jaw bone, the bioelectric activity of masticatory muscles, regional blood flow and microcirculation in the dental pulp and periodontal tissues. LDF and OTO methods estimated fluctuations of saturation level and oxygen transport in microvasculature of periodontal tissues. With LFD identified changes in the concentration of enzymes (nicotinamide, flavins, lipofuscin, porphyrins) involved in metabolic processes Conclusion. Our preliminary results confirmed feasibility and safety the of intraoral ultrasound densitometry technique in the density of bone tissue of periodontium. Conclusion. Application of the diagnostic complex of above mentioned highly informative functional methods allows to perform a multifactorial analysis of the dental status and to prescribe complex etiopathogenetic treatment.

Keywords: electromyography (EMG), reodentography (RDG), laser Doppler flowmetry (LDF), reoperiodontography method (RPG), vital computer capillaroscopy (VCC), optical tissue oximetry (OTO), laser fluorescence diagnosis (LFD)

Procedia PDF Downloads 280

Authors: In-Tsang Lin, Chiching Wei

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Reading order is an important task in many digitization scenarios involving the preservation of the logical structure of a document. From the paper survey, it finds that the state-of-the-art algorithm could not fulfill to get the accurate reading order in the portable document format (PDF) files with rich formats, diverse layout arrangement. In recent years, most of the studies on the analysis of reading order have targeted the specific problem of associating layout components with logical labels, while less attention has been paid to the problem of extracting relationships the problem of detecting the reading order relationship between logical components, such as cross-references. Over 3 years of development, the company Foxit has demonstrated the layout recognition (LR) engine in revision 20601 to eager for the accuracy of the reading order. The bounding box of each paragraph can be obtained correctly by the Foxit LR engine, but the result of reading-order is not always correct for single-column, and two-column layout format due to the table issue, formula issue, and multiple mini separated bounding box and footer issue. Thus, the algorithm is developed to improve the accuracy of the reading order based on the Foxit LR structure. In this paper, a creative observation method (Here called the MESH method) is provided here to open a new chance in the research of the reading-order field. Here two important parameters are introduced, one parameter is the number of the bounding box on the right side of the present bounding box (NRight), and another parameter is the number of the bounding box under the present bounding box (Nunder). And the normalized x-value (x/the whole width), the normalized y-value (y/the whole height) of each bounding box, the x-, and y- position of each bounding box were also put into consideration. Initial experimental results of single column layout format demonstrate a 19.33% absolute improvement in accuracy of the reading-order over 7 PDF files (total 150 pages) using our proposed method based on the LR structure over the baseline method using the LR structure in 20601 revision, which its accuracy of the reading-order is 72%. And for two-column layout format, the preliminary results demonstrate a 44.44% absolute improvement in accuracy of the reading-order over 2 PDF files (total 18 pages) using our proposed method based on the LR structure over the baseline method using the LR structure in 20601 revision, which its accuracy of the reading-order is 0%. Until now, the footer issue and a part of multiple mini separated bounding box issue can be solved by using the MESH method. However, there are still three issues that cannot be solved, such as the table issue, formula issue, and the random multiple mini separated bounding boxes. But the detection of the table position and the recognition of the table structure are out of the scope in this paper, and there is needed another research. In the future, the tasks are chosen- how to detect the table position in the page and to extract the content of the table.

Keywords: document processing, reading order, observation method, layout recognition

Procedia PDF Downloads 181

Authors: Jurriaan Gillissen

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

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

Procedia PDF Downloads 224

Authors: C. Watson, T. Glare, M. O'Callaghan, M. Hurst

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The endemic New Zealand grass grub (Costelytra giveni, Coleoptera: Scarabaeidae) is an economically significant grassland pest in New Zealand. Due to their impacts on production within the agricultural sector, one of New Zealand's primary industries, several methods are being used to either control or prevent the establishment of new grass grub populations in the pasture. One such method involves the use of a biopesticide based on the bacterium Serratia entomophila. This species is one of the causative agents of amber disease, a chronic disease of the larvae which results in death via septicaemia after approximately 2 to 3 months. The ability of S. entomophila to cause amber disease is dependant upon the presence of the amber disease associated plasmid (pADAP), which encodes for the key virulence determinants required for the establishment and maintenance of the disease. Following the collapse of grass grub populations within the soil, resulting from either natural population build-up or application of the bacteria, non-pathogenic plasmid-free Serratia strains begin to predominate within the soil. Whilst the interactions between S. entomophila and grass grub larvae are well studied, less information is known on the interactions between plasmid-bearing and plasmid-free strains, particularly the potential impact of these interactions upon the efficacy of an applied biopesticide. Using a range of constructed strains with antibiotic tags, in vitro (broth culture) and in vivo (soil and larvae) experiments were conducted using inoculants comprised of differing ratios of isogenic pathogenic and non-pathogenic Serratia strains, enabling the relative growth of pADAP+ and pADAP- strains under competition conditions to be assessed. In nutrient-rich, the non-pathogenic pADAP- strain outgrew the pathogenic pADAP+ strain by day 3 when inoculated in equal quantities, and by day 5 when applied as the minority inoculant, however, there was an overall gradual decline in the number of viable bacteria for both strains over a 7-day period. Similar results were obtained in additional experiments using the same strains and continuous broth cultures re-inoculated at 24-hour intervals, although in these cultures, the viable cell count did not diminish over the 7-day period. When the same ratios were assessed in soil microcosms with limited available nutrients, the strains remained relatively stable over a 2-month period. Additionally, in vivo grass grub co-infections assays using the same ratios of tagged Serratia strains revealed similar results to those observed in the soil, but there was also evidence of horizontal transfer of pADAP from the pathogenic to the non-pathogenic strain within the larval gut after a period of 4 days. Whilst the influence of competition is more apparent in broth cultures than within the soil or larvae, further testing is required to determine whether this competition between pathogenic and non-pathogenic Serratia strains has any influence on efficacy and disease progression, and how this may impact on the ability of S. entomophila to cause amber disease within grass grub larvae when applied as a biopesticide.

Keywords: biological control, entomopathogen, microbial ecology, New Zealand

Procedia PDF Downloads 156

Authors: Brajendra S. Sengar, Vivek Garg, Gaurav Siddharth, Nisheka Anadkat, Amitesh Kumar, Shaibal Mukherjee

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The optimal band gap (~ 1 to 1.5 eV) and high absorption coefficient ~104 cm⁻¹ has made Cu₂ZnSn(S,Se)₄ (CZTSSe) films as one of the most promising absorber materials in thin-film photovoltaics. Additionally, CZTSSe consists of elements that are abundant and non-toxic, makes it even more favourable. The CZTSSe thin films are grown at 100 to 500ᵒC substrate temperature (Tsub) on Soda lime glass (SLG) substrate by Elettrorava dual ion beam sputtering (DIBS) system by utilizing a target at 2.43x10⁻⁴ mbar working pressure with RF power of 45 W in argon ambient. The chemical composition, depth profiling, structural properties and optical properties of these CZTSSe thin films prepared on SLG were examined by energy dispersive X-ray spectroscopy (EDX, Oxford Instruments), Hiden secondary ion mass spectroscopy (SIMS) workstation with oxygen ion gun of energy up to 5 keV, X-ray diffraction (XRD) (Rigaku Cu Kα radiation, λ=.154nm) and Spectroscopic Ellipsometry (SE, M-2000D from J. A. Woollam Co., Inc). It is observed that from that, the thin films deposited at Tsub=200 and 300°C show Cu-poor and Zn-rich states (i.e., Cu/(Zn + Sn) < 1 and Zn/Sn > 1), which is not the case for films grown at other Tsub. It has been reported that the CZTSSe thin films with the highest efficiency are typically at Cu-poor and Zn-rich states. The values of band gap in the fundamental absorption region of CZTSSe are found to be in the range of 1.23-1.70 eV depending upon the Cu/(Zn+Sn) ratio. It is also observed that there is a decline in optical band gap with the increase in Cu/(Zn+Sn) ratio (evaluated from EDX measurement). Cu-poor films are found to have higher optical band gap than Cu-rich films. The decrease in the band gap with the increase in Cu content in case of CZTSSe films may be attributed to changes in the extent of p-d hybridization between Cu d-levels and (S, Se) p-levels. CZTSSe thin films with Cu/(Zn+Sn) ratio in the range 0.86–1.5 have been successfully deposited using DIBS. Optical band gap of the films is found to vary from 1.23 to 1.70 eV based on Cu/(Zn+Sn) ratio. CZTSe films with Cu/ (Zn+Sn) ratio of .86 are found to have optical band gap close to the ideal band gap (1.49 eV) for highest theoretical conversion efficiency. Thus by tailoring the value of Cu/(Zn+Sn), CZTSSe thin films with the desired band gap could be obtained. Acknowledgment: We are thankful to DIBS, EDX, and XRD facility equipped at Sophisticated Instrument Centre (SIC) at IIT Indore. The authors B. S. S and A. K. acknowledge CSIR, and V. G. acknowledges UGC, India for their fellowships. B. S. S is thankful to DST and IUSSTF for BASE Internship Award. Prof. Shaibal Mukherjee is thankful to DST and IUSSTF for BASE Fellowship and MEITY YFRF award. This work is partially supported by DAE BRNS, DST CERI, and DST-RFBR Project under India-Russia Programme of Cooperation in Science and Technology. We are thankful to Mukul Gupta for SIMS facility equipped at UGC-DAE Indore.

Keywords: CZTSSe, DIBS, EDX, solar cell

Procedia PDF Downloads 250

Authors: Malkhaz Jokhadze, Vakhtang Mshvildadze, Levan Makaradze, Ekaterine Mosidze, Salome Barbaqadze, Mariam Murtazashvili, Dali Berashvili, Koba sivsivadze, Lasha Bakuridze, Aliosha Bakuridze

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Essential oils are one of the most important groups of biologically active substances present in plants. Due to the chemical diversity of components, essential oils and their preparations have a wide spectrum of pharmacological action. They have bactericidal, antiviral, fungicidal, antiprotozoal, anti-inflammatory, spasmolytic, sedative and other activities. They are expectorant, spasmolytic, sedative, hypotensive, secretion enhancing, antioxidant remedies. Based on preliminary pharmacological studies, we have developed a formulation called “Phytobiotic” containing essential oils, a feed additive for poultry as an alternative to antibiotics. Phytobiotic is a water-soluble powder containing a composition of essential oils of thyme, clary, monarda and auxiliary substances: dry extract of liquorice and inhalation lactose. On this stage of research, the goal was to study the chemical composition of provided phytobiotic, identify the main substances and determine their quantity, investigate the biological activity of phytobiotic through in vitro and in vivo studies. Using gas chromatography-mass spectrometry, 38 components were identified in phytobiotic, representing acyclic-, monocyclic-, bicyclic-, and sesquiterpenes. Together with identification of main active substances, their quantitative content was determined, including acyclic terpene alcohol β-linalool, acyclic terpene ketone linalyl acetate, monocyclic terpenes: D-limonene and γ-terpinene, monocyclic aromatic terpene thymol. Provided phytobiotic has pronounced and at the same time broad spectrum of antibacterial activity. In the cell model, phytobiotic showed weak antioxidant activity, and it was stronger in the ORAC (chemical model) tests. Meanwhile anti-inflammatory activity was also observed. When fowls were supplied feed enriched with phytobiotic, it was observed that gained weight of the chickens in the experimental group exceeded the same data for the control group during the entire period of the experiment. The survival rate of broilers in the experimental group during the growth period was 98% compared to -94% in the control group. As a result of conducted researches probable four different mechanisms which are important for the action of phytobiotics were identified: sensory, metabolic, antioxidant and antibacterial action. General toxic, possible local irritant and allergenic effects of phytobiotic were also investigated. Performed assays proved that formulation is safe.

Keywords: clary, essential oils, monarda, poultry, phytobiotics, thyme

Procedia PDF Downloads 171

Authors: Celine Bonnaud, Isabelle Billard, Nicolas Papaiconomou, Eric Chainet

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Thanks to their high magnetization and low mass, permanent magnets (NdFeB and SmCo) have quickly became essential for new energies (wind turbines, electrical vehicles…). They contain large quantities of neodymium, samarium and dysprosium, that have been recently classified as critical elements and that therefore need to be recycled. Electrochemical processes including electrodissolution followed by electrodeposition are an elegant and environmentally friendly solution for the recycling of such lanthanides contained in permanent magnets. However, electrochemistry of the lanthanides is a real challenge as their standard potentials are highly negative (around -2.5V vs ENH). Consequently, non-aqueous solvents are required. Ionic liquids (IL) are novel electrolytes exhibiting physico-chemical properties that fulfill many requirements of the sustainable chemistry principles, such as extremely low volatility and non-flammability. Furthermore, their chemical and electrochemical properties (solvation of metallic ions, large electrochemical windows, etc.) render them very attractive media to implement alternative and sustainable processes in view of integrated processes. All experiments that will be presented were carried out using butyl-methylpyrrolidinium bis(trifluoromethanesulfonyl)imide. Linear sweep, cyclic voltammetry and potentiostatic electrochemical techniques were used. The reliability of electrochemical experiments, performed without glove box, for the classic three electrodes cell used in this study has been assessed. Deposits were obtained by chronoamperometry and were characterized by scanning electron microscopy and energy-dispersive X-ray spectroscopy. The IL cathodic behavior under different constraints (argon, nitrogen, oxygen atmosphere or water content) and using several electrode materials (Pt, Au, GC) shows that with argon gas flow and gold as a working electrode, the cathodic potential can reach the maximum value of -3V vs Fc+/Fc; thus allowing a possible reduction of lanthanides. On a gold working electrode, the reduction potential of samarium and neodymium was found to be -1.8V vs Fc+/Fc while that of dysprosium was -2.1V vs Fc+/Fc. The individual deposits obtained were found to be porous and presented some significant amounts of C, N, F, S and O atoms. Selective deposition of neodymium in presence of dysprosium was also studied and will be discussed. Next, metallic Sm, Nd and Dy electrodes were used in replacement of Au, which induced changes in the reduction potential values and the deposit structures of lanthanides. The individual corrosion potentials were also measured in order to determine the parameters influencing the electrodissolution of these metals. Finally, a full recycling process was investigated. Electrodissolution of a real permanent magnet sample was monitored kinetically. Then, the sequential electrodeposition of all lanthanides contained in the IL was investigated. Yields, quality of the deposits and consumption of chemicals will be discussed in depth, in view of the industrial feasibility of this process for real permanent magnets recycling.

Keywords: electrodeposition, electrodissolution, ionic liquids, lanthanides, rcycling

Procedia PDF Downloads 274

Authors: Wei-Chih Huang, Pei-Lung Chung, Ching-Heng Lin, Hsuan-Chia Yang, Der-Ming Liou

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Background: In-Hospital Cardiac Arrest (IHCA) threaten life of the inpatients, cause serious effect to patient safety, quality of inpatients care and hospital service. Health providers must identify the signs of IHCA early to avoid the occurrence of IHCA. This study will consider the potential association between early signs of IHCA and the essence of patient care provided by nurses and other professionals before an IHCA occurs. The aim of this study is to identify significant associations between nursing interventions and abnormal early evaluation results of IHCA that can assist health care providers in monitoring inpatients at risk of IHCA to increase opportunities of IHCA early detection and prevention. Materials and Methods: This study used one of the data mining techniques called association rules mining to compute associations between nursing interventions and abnormal early evaluation results of IHCA. The nursing interventions and abnormal early evaluation results of IHCA were considered to be co-occurring if nursing interventions were provided within 24 hours of last being observed in abnormal early evaluation results of IHCA. The rule based methods were utilized 23.6 million electronic medical records (EMR) from a medical center in Taipei, Taiwan. This dataset includes 733 concepts of nursing interventions that coded by clinical care classification (CCC) codes and 13 early evaluation results of IHCA with binary codes. The values of interestingness and lift were computed as Q values to measure the co-occurrence and associations’ strength between all in-hospital patient care measures and abnormal early evaluation results of IHCA. The associations were evaluated by comparing the results of Q values and verified by medical experts. Results and Conclusions: The results show that there are 4195 pairs of associations between nursing interventions and abnormal early evaluation results of IHCA with their Q values. The indication of positive association is 203 pairs with Q values greater than 5. Inpatients with high blood sugar level (hyperglycemia) have positive association with having heart rate lower than 50 beats per minute or higher than 120 beats per minute, Q value is 6.636. Inpatients with temporary pacemaker (TPM) have significant association with high risk of IHCA, Q value is 47.403. There is significant positive correlation between inpatients with hypovolemia and happened abnormal heart rhythms (arrhythmias), Q value is 127.49. The results of this study can help to prevent IHCA from occurring by making health care providers early recognition of inpatients at risk of IHCA, assist with monitoring patients for providing quality of care to patients, improve IHCA surveillance and quality of in-hospital care.

Keywords: in-hospital cardiac arrest, patient safety, nursing intervention, association rule mining

Procedia PDF Downloads 271

Authors: Mustafa M. Donma, Orkide Donma

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Iron is physiologically essential. However, it also participates in the catalysis of free radical formation reactions. Its deficiency is associated with amplified health risks. This trace element establishes some links with another physiological process related to cell death, apoptosis. Both iron deficiency and iron overload are closely associated with apoptosis. Soluble tumor necrosis factor-like weak inducer of apoptosis (sTWEAK) has the ability to trigger apoptosis and plays a dual role in the physiological versus pathological inflammatory responses of tissues. The aim of this study was to investigate the status of these parameters as well as the associations among them in children with obesity, a low-grade inflammatory state. The study was performed on groups of children with normal body mass index (N-BMI) and obesity. Forty-three children were included in each group. Based upon age- and sex-adjusted BMI percentile tables prepared by World Health Organization, children whose values varied between 85 and 15 were included in N-BMI group. Children whose BMI percentile values were between 99 and 95 comprised obese (OB) group. Institutional ethical committee approval and informed consent forms were taken prior to the study. Anthropometric measurements (weight, height, waist circumference, hip circumference, head circumference, neck circumference) and blood pressure values (systolic blood pressure and diastolic blood pressure) were recorded. Routine biochemical analysis including serum iron, total iron binding capacity (TIBC), transferrin saturation percent (Tf Sat %), and ferritin were performed. Soluble tumor necrosis factor-like weak inducer of apoptosis levels were determined by enzyme-linked immunosorbent assay. Study data was evaluated using appropriate statistical tests performed by the statistical program SPSS. Serum iron levels were 91±34 mcrg/dl and 75±31 mcrg/dl in N-BMI and OB children, respectively. The corresponding values for TIBC, Tf Sat %, ferritin were 265 mcrg/dl vs 299 mcrg/dl, 37.2±19.1 % vs 26.7±14.6 %, and 41±25 ng/ml vs 44±26 ng/ml. in N-BMI and OB groups, sTWEAK concentrations were measured as 351 ng/L and 325 ng/L, respectively (p>0.05). Correlation analysis revealed significant associations between sTWEAK levels and iron related parameters (p<0.05) except ferritin. In conclusion, iron contributes to apoptosis. Children with iron deficiency have decreased apoptosis rate in comparison with that of healthy children. sTWEAK is inducer of apoptosis. Obese children had lower levels of both iron and sTWEAK. Low levels of sTWEAK are associated with several types of cancers and poor survival. Although iron deficiency state was not observed in this study, the correlations detected between decreased sTWEAK and decreased iron as well as Tf Sat % values were valuable findings, which point out decreased apoptosis. This may induce a proinflammatory state, potentially leading to malignancies in the future lives of obese children.

Keywords: apoptosis, children, iron-related parameters, obesity, soluble tumor necrosis factor-like weak inducer of apoptosis

Procedia PDF Downloads 132

Authors: Nilufar Chowdhury, Fereydoun Najafian Jazi, Omid Ghasemi-Fare

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The thermal effect on soil properties induces significant variations in hydraulic conductivity, which is attributable to temperature-dependent transitions in soil properties. With the elevation of temperature, there can be a notable increase in intrinsic permeability due to the degeneration of bound water molecules into a free state facilitated by thermal energy input. Conversely, thermal consolidation may cause a reduction in intrinsic permeability as soil particles undergo densification. This thermal response of soil permeability exhibits pronounced heterogeneity across different soil types. Furthermore, this temperature-induced disruption of the bound water within clay matrices can enhance the mineral-to-mineral contact, initiating irreversible deformation within the clay structure. This indicates that when soil undergoes heating-cooling cycles, plastic strain can develop, which needs to be investigated for every soil type to understand the thermo-hydro mechanical behavior of clay properly. This research aims to study the effect of the heating-cooling cycle on the intrinsic permeability and time-dependent evaluation of thermal volume change of sodium Bentonite clay. A temperature-controlled triaxial permeameter cell is used in this study. The selected temperature is 20° C, 40° C, 40° C and 80° C. The hydraulic conductivity of Bentonite clay under 100 kPa confining stresses was measured. Hydraulic conductivity analysis was performed on a saturated sample for a void ratio e = 0.9, corresponding to a dry density of 1.2 Mg/m3. Different hydraulic gradients were applied between the top and bottom of the sample to obtain a measurable flow through the sample. The hydraulic gradient used for the experiment was 4000. The diameter and thickness of the sample are 101. 6 mm, and 25.4 mm, respectively. Both for heating and cooling, the hydraulic conductivity at each temperature is measured after the flow reaches the steady state condition to make sure the volume change due to thermal loading is stabilized. Thus, soil specimens were kept at a constant temperature during both the heating and cooling phases for at least 10-18 days to facilitate the equilibration of hydraulic transients. To assess the influence of temperature-induced volume changes of Bentonite clay, the evaluation of void ratio change during this time period has been monitored. It is observed that the intrinsic permeability increases by 30-40% during the heating cycle. The permeability during the cooling cycle is 10-12% lower compared to the permeability observed during the heating cycle at a particular temperature. This reduction in permeability implies a change in soil fabric due to the thermal effect. An initial increase followed by a rapid decrease in void ratio was observed, representing the occurrence of possible osmotic swelling phenomena followed by thermal consolidation. It has been observed that after a complete heating-cooling cycle, there is a significant change in the void ratio compared to the initial void ratio of the sample. The results obtained suggest that Bentonite clay’s microstructure can change subject to a complete heating-cooling process, which regulates macro behavior such as the permeability of Bentonite clay.

Keywords: bentonite, permeability, temperature, thermal volume change

Procedia PDF Downloads 49

Authors: Antoni Grau, Yolanda Bolea, Alberto Sanfeliu

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Mobile robots can be used in many different applications, including mapping, search, rescue, reconnaissance, hazard detection, and carpet cleaning, exploration, etc. However, they are limited due to their reliance on traditional energy sources such as electricity and oil which cannot always provide a convenient energy source in all situations. In an ever more eco-conscious world, solar energy offers the most environmentally clean option of all energy sources. Electricity presents threats of pollution resulting from its production process, and oil poses a huge threat to the environment. Not only does it pose harm by the toxic emissions (for instance CO2 emissions), it produces the combustion process necessary to produce energy, but there is the ever present risk of oil spillages and damages to ecosystems. Solar energy can help to mitigate carbon emissions by replacing more carbon intensive sources of heat and power. The challenge of this work is to propose the design and the implementation of electric battery recharge stations. Those recharge docks are based on the use of renewable energy such as solar energy (with photovoltaic panels) with the object to reduce the CO2 emissions. In this paper, a comparative study of the CO2 emission productions (from the use of different energy sources: natural gas, gas oil, fuel and solar panels) in the charging process of the Segway PT batteries is carried out. To make the study with solar energy, a photovoltaic panel, and a Buck-Boost DC/DC block has been used. Specifically, the STP005S-12/Db solar panel has been used to carry out our experiments. This module is a 5Wp-photovoltaic (PV) module, configured with 36 monocrystalline cells serially connected. With those elements, a battery recharge station is made to recharge the robot batteries. For the energy storage DC/DC block, a series of ultracapacitors have been used. Due to the variation of the PV panel with the temperature and irradiation, and the non-integer behavior of the ultracapacitors as well as the non-linearities of the whole system, authors have been used a fractional control method to achieve that solar panels supply the maximum allowed power to recharge the robots in the lesser time. Greenhouse gas emissions for production of electricity vary due to regional differences in source fuel. The impact of an energy technology on the climate can be characterised by its carbon emission intensity, a measure of the amount of CO2, or CO2 equivalent emitted by unit of energy generated. In our work, the coal is the fossil energy more hazardous, providing a 53% more of gas emissions than natural gas and a 30% more than fuel. Moreover, it is remarkable that existing fossil fuel technologies produce high carbon emission intensity through the combustion of carbon-rich fuels, whilst renewable technologies such as solar produce little or no emissions during operation, but may incur emissions during manufacture. The solar energy thus can help to mitigate carbon emissions.

Keywords: autonomous robots, CO2 emissions, DC/DC buck-boost, solar energy

Procedia PDF Downloads 422

Authors: V. T. Gerov, D. I. Gerova, I. D. Micheva, N. F. Nazifova-Tasinova, M. N. Nikolova, M. G. Pasheva, B. T. Galunska

Abstract:

Multiple myeloma (MM) is the most frequent plasma cell (PC) dyscrasia that involves the skeleton. Myeloma bone disease (MBD) is characterized by osteolytic bone lesions as a result of increased osteoclasts activity not followed by reactive bone formation due to osteoblasts suppression. Skeletal complications cause significant adverse effects on quality of life and lead to increased morbidity and mortality. Last decade studies revealed the implication of different proteins in osteoclast activation and osteoblast inhibition. The aim of the present study was to determine serum levels of periostin, sRANKL and osteopontin and to evaluate their role as bone markers in MBD. Materials and methods. Thirty-two newly diagnosed MM patients (mean age: 62.2 ± 10.7 years) and 33 healthy controls (mean age: 58.9 ± 7.5 years) were enrolled in the study. According to IMWG criteria 28 patients were with symptomatic MM and 4 with monoclonal gammopathy of undetermined significance (MGUS). In respect to their bone involvement all symptomatic patients were divided into two groups (G): 9 patients with 0-3 osteolytic lesions (G1) and 19 patients with >3 osteolytic lesions and/or pathologic fractures (G2). Blood samples were drawn for routine laboratory analysis and for measurement of periostin, sRANKL and osteopontin serum levels by ELISA kits (Shanghai Sunred Biological Technology, China). Descriptive analysis, Mann-Whitney test for assessment the differences between groups and non-parametric correlation analysis were performed using GraphPad Prism v8.01. Results. The median serum levels of periostin, sRANKL and osteopontin of ММ patients were significantly higher compared to controls (554.7pg/ml (IQR=424.0-720.6) vs 396.9pg/ml (IQR=308.6-471.9), p=0.0001; 8.9pg/ml (IQR=7.1-10.5) vs 5.6pg/ml (IQR=5.1-6.4, p<0.0001 and 514.0ng/ml (IQR=469.3-754.0) vs 387.0ng/ml (IQR=335.9-441.9), p<0.0001, respectively). for assessment of differences between groups and non-parametric correlation analysis were performed using GraphPad Prism v8.01. Statistical significance was found for all tested bone markers between symptomatic MM patients and controls: G1 vs controls (p<0.03), G2 vs controls (p<0.0001) for periostin; G1 vs controls (p<0.0001), G2 vs controls (p<0.0001) for sRANKL; G1 vs controls (p=0.002), G2 vs controls (p<0.0001) for osteopontin, as well between symptomatic MM patients and MGUS patients: G1 vs MGUS (p<0.003), G2 vs MGUS (p=0.003) for periostin; G1 vs MGUS (p<0.05), G2 vs MGUS (p<0.001) for sRANKL; G1 vs MGUS (p=0.011), G2 vs MGUS (p=0.0001) for osteopontin. No differences were detected between MGUS and controls and between patients in G1 and G2 groups. Spearman correlation analysis revealed moderate positive correlation between periostin and beta-2-microglobulin (r=0.416, p=0.018), percentage bone marrow myeloma PC (r=0.432, p=0.014), and serum total protein (r=0.427, p=0.015). Osteopontin levels were also positively related to beta-2-microglobulin (r=0.540, p=0.0014), percentage bone marrow myeloma PC (r=0.423, p=0.016), and serum total protein (r=0.413, p=0.019). Serum sRANKL was only related to beta-2-microglobulin levels (r=0.398, p=0.024). Conclusion: In the present study, serum levels of periostin, sRANKL and osteopontin in newly diagnosed MM patients were evaluated. They gradually increased from MGUS to more advanced stages of MM reflecting the severity of bone destruction. These results support the idea that some new protein markers could be used in monitoring the MBD as a most severe complication of MM.

Keywords: myeloma bone disease, periostin, sRANKL, osteopontin

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Authors: Federico Herrera, Valle Gomez García de Soria, Itxaso Portero Sainz, Carlos Fernández Arandojo, Mercedes Royg, Ana Marcos Jimenez, Anna Kreutzman, Cecilia MuñozCalleja

Abstract:

Introduction: Graft-versus-host disease (GVHD) still remains the major complication associated with allogeneic stem cell transplantation (SCT). The pathogenesis involves migration of donor naïve T-cells into recipient secondary lymphoid organs. Two molecules are important in this process: CD62L and CCR7, which are characteristically expressed in naïve/central memory T-cells. With this background, we aimed to study the influence of CCR7 and CD62L on donor lymphocytes in the development and severity of GVHD. Material and methods: This single center study included 98 donor-recipient pairs. Samples were collected prospectively from the apheresis product and phenotyped by flow cytometry. CCR7 and CD62L expression in CD4+ and CD8+ T-cells were compared between patients who developed acute (n=40) or chronic GVHD (n=33) and those who did not (n=38). Results: The patients who developed acute GVHD were transplanted with a higher percentage of CCR7+CD4+ T-cells (p = 0.05) compared to the no GVHD group. These results were confirmed when these patients were divided in degrees according to the severity of the disease; the more severe disease, the higher percentage of CCR7+CD4+ T-cells. Conversely, chronic GVHD patients received a higher percentage of CCR7+CD8+ T-cells (p=0.02) in comparison to those who did not develop the complication. These data were also confirmed when patients were subdivided in degrees of the disease severity. A multivariable analysis confirmed that percentage of CCR7+CD4+ T-cells is a predictive factor of acute GVHD whereas the percentage of CCR7+CD8+ T-cells is a predictive factor of chronic GVHD. In vitro functional assays (migration and activation assays) supported the idea of CCR7+ T-cells were involved in the development of GVHD. As low levels of CD62L expression were detected in all apheresis products, we tested the hypothesis that CD62L was shed during apheresis procedure. Comparing CD62L surface levels in T-cells from the same donor immediately before collecting the apheresis product, and the final apheresis product we found that this process down-regulated CD62L in both CD4+ and CD8+ T cells (p=0.008). Interestingly, when CD62L levels were analysed in days 30 or 60 after engraftment, they recovered to baseline (p=0.008). However, to investigate the relation between CD62L expression and the development of GVHD in the recipient samples after the engraftment, no differences were observed comparing patients with GVHD to those who did not develop the disease. Discussion: Our prospective study indicates that the CCR7+ T-cells from the donor, which include naïve and central memory T-cells, contain the alloreactive cells with a high ability to mediate GVHD (in the case of both migration and activation). Therefore we suggest that the proportion and functional properties of CCR7+CD4+ and CCR7+CD8+ T-cells in the apheresis could act as a predictive biomarker to both acute and chronic GVHD respectively. Importantly, our study precludes that CD62L is lost in the apheresis and therefore it is not a reliable biomarker for the development of GVHD.

Keywords: CCR7, CD62L, GVHD, SCT

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Authors: Ioanna Taouki, Marie Lallier, David Soto

Abstract:

Metacognition refers to the capacity to reflect upon our own cognitive processes. Although there is an ongoing discussion in the literature on the role of metacognition in learning and academic achievement, little is known about its neurodevelopmental trajectories in early childhood, when children begin to receive formal education in reading. Here, we evaluate the metacognitive ability, estimated under a recently developed Signal Detection Theory model, of a cohort of children aged between 6 and 7 (N=60), who performed three two-alternative-forced-choice tasks (two linguistic: lexical decision task, visual attention span task, and one non-linguistic: emotion recognition task) including trial-by-trial confidence judgements. Our study has three aims. First, we investigated how metacognitive ability (i.e., how confidence ratings track accuracy in the task) relates to performance in general standardized tasks related to students' reading and general cognitive abilities using Spearman's and Bayesian correlation analysis. Second, we assessed whether or not young children recruit common mechanisms supporting metacognition across the different task domains or whether there is evidence for domain-specific metacognition at this early stage of development. This was done by examining correlations in metacognitive measures across different task domains and evaluating cross-task covariance by applying a hierarchical Bayesian model. Third, using robust linear regression and Bayesian regression models, we assessed whether metacognitive ability in this early stage is related to the longitudinal learning of children in a linguistic and a non-linguistic task. Notably, we did not observe any association between students’ reading skills and metacognitive processing in this early stage of reading acquisition. Some evidence consistent with domain-general metacognition was found, with significant positive correlations between metacognitive efficiency between lexical and emotion recognition tasks and substantial covariance indicated by the Bayesian model. However, no reliable correlations were found between metacognitive performance in the visual attention span and the remaining tasks. Remarkably, metacognitive ability significantly predicted children's learning in linguistic and non-linguistic domains a year later. These results suggest that metacognitive skill may be dissociated to some extent from general (i.e., language and attention) abilities and further stress the importance of creating educational programs that foster students’ metacognitive ability as a tool for long term learning. More research is crucial to understand whether these programs can enhance metacognitive ability as a transferable skill across distinct domains or whether unique domains should be targeted separately.

Keywords: confidence ratings, development, metacognitive efficiency, reading acquisition

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Authors: Ambali Alade Odebowale, Andargachew Mekonnen Berhe, Haroldo T. Hattori, Andrey E. Miroshnichenko

Abstract:

Solar thermophotovoltaic systems (STPV) have emerged as a promising solution to overcome the Shockley-Queisser limit, a significant impediment in the direct conversion of solar radiation into electricity using conventional solar cells. The STPV system comprises essential components such as an optical concentrator, selective emitter, and a thermophotovoltaic (TPV) cell. The pivotal element in achieving high efficiency in an STPV system lies in the design of a spectrally selective emitter or absorber. Traditional methods for designing and optimizing selective emitters are often time-consuming and may not yield highly selective emitters, posing a challenge to the overall system performance. In recent years, the application of machine learning techniques in various scientific disciplines has demonstrated significant advantages. This paper proposes a novel nanostructure composed of four-layered materials (SiC/W/SiO2/W) to function as a selective emitter in the energy conversion process of an STPV system. Unlike conventional approaches widely adopted by researchers, this study employs a machine learning-based approach for the design and optimization of the selective emitter. Specifically, a random forest algorithm (RFA) is employed for the design of the selective emitter, while the optimization process is executed using genetic algorithms. This innovative methodology holds promise in addressing the challenges posed by traditional methods, offering a more efficient and streamlined approach to selective emitter design. The utilization of a machine learning approach brings several advantages to the design and optimization of a selective emitter within the STPV system. Machine learning algorithms, such as the random forest algorithm, have the capability to analyze complex datasets and identify intricate patterns that may not be apparent through traditional methods. This allows for a more comprehensive exploration of the design space, potentially leading to highly efficient emitter configurations. Moreover, the application of genetic algorithms in the optimization process enhances the adaptability and efficiency of the overall system. Genetic algorithms mimic the principles of natural selection, enabling the exploration of a diverse range of emitter configurations and facilitating the identification of optimal solutions. This not only accelerates the design and optimization process but also increases the likelihood of discovering configurations that exhibit superior performance compared to traditional methods. In conclusion, the integration of machine learning techniques in the design and optimization of a selective emitter for solar thermophotovoltaic systems represents a groundbreaking approach. This innovative methodology not only addresses the limitations of traditional methods but also holds the potential to significantly improve the overall performance of STPV systems, paving the way for enhanced solar energy conversion efficiency.

Keywords: emitter, genetic algorithm, radiation, random forest, thermophotovoltaic

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Authors: M. Nerantzaki, I. Koliakou, D. Bikiaris

Abstract:

This study evaluates the hypothesis that the incorporation of fibrous hydroxyapatite nanoparticles (nHA) with high crystallinity and high aspect ratio, synthesized by hydrothermal method, into Poly(butylene succinate) (PBSu), improves the bioactivity of the aliphatic polyester and affects new bone growth inhibiting resorption and enhancing bone formation. Hydroxyapatite nanorods were synthesized using a simple hydrothermal procedure. First, the HPO42- -containing solution was added drop-wise into the Ca2+-containing solution, while the molar ratio of Ca/P was adjusted at 1.67. The HA precursor was then treated hydrothermally at 200°C for 72 h. The resulting powder was characterized using XRD, FT-IR, TEM, and EDXA. Afterwards, PBSu nanocomposites containing 2.5wt% (nHA) were prepared by in situ polymerization technique for the first time and were examined as potential scaffolds for bone engineering applications. For comparison purposes composites containing either 2.5wt% micro-Bioglass (mBG) or 2.5wt% mBG-nHA were prepared and studied, too. The composite scaffolds were characterized using SEM, FTIR, and XRD. Mechanical testing (Instron 3344) and Contact Angle measurements were also carried out. Enzymatic degradation was studied in an aqueous solution containing a mixture of R. Oryzae and P. Cepacia lipases at 37°C and pH=7.2. In vitro biomineralization test was performed by immersing all samples in simulated body fluid (SBF) for 21 days. Biocompatibility was assessed using rat Adipose Stem Cells (rASCs), genetically modified by nucleofection with DNA encoding SB100x transposase and pT2-Venus-neo transposon expression plasmids in order to attain fluorescence images. Cell proliferation and viability of cells on the scaffolds were evaluated using fluoresce microscopy and MTT (3-(4,5-dimethylthiazol-2-yl)-2,5 diphenyltetrazolium bromide) assay. Finally, osteogenic differentiation was assessed by staining rASCs with alizarine red using cetylpyridinium chloride (CPC) method. TEM image of the fibrous HAp nanoparticles, synthesized in the present study clearly showed the fibrous morphology of the synthesized powder. The addition of nHA decreased significantly the contact angle of the samples, indicating that the materials become more hydrophilic and hence they absorb more water and subsequently degrade more rapidly. In vitro biomineralization test confirmed that all samples were bioactive as mineral deposits were detected by X-ray diffractometry after incubation in SBF. Metabolic activity of rASCs on all PBSu composites was high and increased from day 1 of culture to day 14. On day 28 metabolic activity of rASCs cultured on samples enriched with bioceramics was significantly decreased due to possible differentiation of rASCs to osteoblasts. Staining rASCs with alizarin red after 28 days in culture confirmed our initial hypothesis as the presence of calcium was detected, suggesting osteogenic differentiation of rACS on PBSu/nHAp/mBG 2.5% and PBSu/mBG 2.5% composite scaffolds.

Keywords: biomaterials, hydroxyapatite nanorods, poly(butylene succinate), scaffolds

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