Search results for: multicolor magnetic particle imaging

Authors: Carolina Zambrana, Grover Zurita

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The food loss production that occurs in deficient agricultural production is one of the major problems worldwide. This puts the population's food security and the efficiency of farming investments at risk. It is to be expected that this food security will be achieved with the own and efficient production of each country. It will have an impact on the well-being of its population and, thus, also on food sovereignty. The production losses in quantity and quality occur due to the lack of efficient detection of diseases at an early stage. It is very difficult to solve the agriculture efficiency using traditional methods since it takes a long time to be carried out due to detection imprecision of the main diseases, especially when the production areas are extensive. Therefore, the main objective of this research study is to perform a systematic literature review, of the latest five years, of Precision Agriculture (PA) to be able to understand the state of the art of the set of new technologies, procedures, and optimization processes with Artificial Intelligence (AI). This study will focus on Corns, Potatoes, and Rice diagnostic diseases. The extensive literature review will be performed on Elsevier, Scopus, and IEEE databases. In addition, this research will focus on advanced digital imaging processing and the development of software and hardware for PA. The convolution neural network will be handling special attention due to its outstanding diagnostic results. Moreover, the studied data will be incorporated with artificial intelligence algorithms for the automatic diagnosis of crop quality. Finally, precision agriculture with technology applied to the agricultural sector allows the land to be exploited efficiently. This system requires sensors, drones, data acquisition cards, and global positioning systems. This research seeks to merge different areas of science, control engineering, electronics, digital image processing, and artificial intelligence for the development, in the near future, of a low-cost image measurement system that allows the optimization of crops with AI.

Keywords: precision agriculture, convolutional neural network, deep learning, artificial intelligence

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Authors: Peter W. Woodruff, Georgios Ponirakis, Reem Ibrahim, Amani Ahmed, Hoda Gad, Ioannis N. Petropoulos, Adnan Khan, Ahmed Elsotouhy, Surjith Vattoth, Mahmoud K. M. Alshawwaf, Mohamed Adil Shah Khoodoruth, Marwan Ramadan, Anjushri Bhagat, James Currie, Ziyad Mahfoud, Hanadi Al Hamad, Ahmed Own, Peter Haddad, Majid Alabdulla, Rayaz A. Malik

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Introduction:- We aimed to test the hypothesis that, using corneal confocal microscopy (a non-invasive method for assessing corneal nerve fibre integrity), patients with schizophrenia would show neuronal abnormalities compared with healthy participants. Schizophrenia is a neurodevelopmental and progressive neurodegenerative disease, for which there are no validated biomarkers. Corneal confocal microscopy (CCM) is a non-invasive ophthalmic imaging biomarker that can be used to detect neuronal abnormalities in neuropsychiatric syndromes. Methods:- Patients with schizophrenia (DSM-V criteria) without other causes of peripheral neuropathy and healthy controls underwent CCM, vibration perception threshold (VPT) and sudomotor function testing. The diagnostic accuracy of CCM in distinguishing patients from controls was assessed using the area under the curve (AUC) of the Receiver Operating Characterstics (ROC) curve. Findings:- Participants with schizophrenia (n=17) and controls (n=38) with comparable age (35.7±8.5 vs 35.6±12.2, P=0.96) were recruited. Patients with schizophrenia had significantly higher body weight (93.9±25.5 vs 77.1±10.1, P=0.02), lower Low Density Lipoproteins (2.6±1.0 vs 3.4±0.7, P=0.02), but comparable systolic and diastolic blood pressure, HbA1c, total cholesterol, triglycerides and High Density Lipoproteins were comparable with control participants. Patients with schizophrenia had significantly lower corneal nerve fiber density (CNFD, fibers/mm2) (23.5±7.8 vs 35.6±6.5, p<0.0001), branch density (CNBD, branches/mm2) (34.4±26.9 vs 98.1±30.6, p<0.0001), and fiber length (CNFL, mm/mm2) (14.3±4.7 vs 24.2±3.9, p<0.0001) but no difference in VPT (6.1±3.1 vs 4.5±2.8, p=0.12) and electrochemical skin conductance (61.0±24.0 vs 68.9±12.3, p=0.23) compared with controls. The diagnostic accuracy of CNFD, CNBD and CNFL to distinguish patients with schizophrenia from healthy controls were, according to the AUC, (95% CI): 87.0% (76.8-98.2), 93.2% (84.2-102.3), 93.2% (84.4-102.1), respectively. Conclusion:- In conclusion, CCM can be used to help identify neuronal changes and has a high diagnostic accuracy to distinguish subjects with schizophrenia from healthy controls.

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Authors: T. Almutairi, K. Naudi, N. Nairn, X. Ju, B. Eng, J. Whitters, A. Ayoub

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Purpose: At present Cone Beam Computed Tomography (CBCT) imaging does not record dental morphology accurately due to the scattering produced by metallic restorations and the reported magnification. The aim of this pilot study is the development and validation of a new method for the replacement of the distorted dentition of CBCT scans with the dental image captured by the digital intraoral camera. Materials and Method: Six dried skulls with orthodontics brackets on the teeth were used in this study. Three intra-oral markers made of dental stone were constructed which were attached to orthodontics brackets. The skulls were CBCT scanned, and occlusal surface was captured using TRIOS® 3D intraoral scanner. Marker based and surface based registrations were performed to fuse the digital intra-oral scan(IOS) into the CBCT models. This produced a new composite digital model of the skull and dentition. The skulls were scanned again using the commercially accurate Laser Faro® arm to produce the 'gold standard' model for the assessment of the accuracy of the developed method. The accuracy of the method was assessed by measuring the distance between the occlusal surfaces of the new composite model and the 'gold standard' 3D model of the skull and teeth. The procedure was repeated a week apart to measure the reproducibility of the method. Results: The results showed no statistically significant difference between the measurements on the first and second occasions. The absolute mean distance between the new composite model and the laser model ranged between 0.11 mm to 0.20 mm. Conclusion: The dentition of the CBCT can be accurately replaced with the dental image captured by the intra-oral scanner to create a composite model. This method will improve the accuracy of orthognathic surgical prediction planning, with the final goal of the fabrication of a physical occlusal wafer without to guide orthognathic surgery and eliminate the need for dental impression.

Keywords: orthognathic surgery, superimposition, models, cone beam computed tomography

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Authors: Sofiya Rao, Sagnik Dey

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Aerosol-cloud-precipitation interaction continues to be one of the largest sources of uncertainty in quantifying the aerosol climate forcing. The uncertainty is increasing from global to regional scale. This problem remains unresolved due to the large discrepancy in the representation of cloud processes in the climate models. Most of the studies on aerosol-cloud-climate interaction and aerosol-cloud-precipitation over Indian Ocean (like INDOEX, CAIPEEX campaign etc.) are restricted to either particular to one season or particular to one region. Here we developed a theoretical framework to quantify aerosol indirect radiative forcing using Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol and cloud products of 15 years (2000-2015) period over the Indian Ocean. This framework relies on the observationally constrained estimate of the aerosol-induced change in cloud albedo. We partitioned the change in cloud albedo into the change in Liquid Water Path (LWP) and Effective Radius of Clouds (Reff) in response to an aerosol optical depth (AOD). Cloud albedo response to an increase in AOD is most sensitive in the range of LWP between 120-300 gm/m² for a range of Reff varying from 8-24 micrometer, which means aerosols are most sensitive to this range of LWP and Reff. Using this framework, aerosol forcing during a transition from indirect to semi-direct effect is also calculated. The outcome of this analysis shows best results over the Arabian Sea in comparison with the Bay of Bengal and the South Indian Ocean because of heterogeneity in aerosol spices over the Arabian Sea. Over the Arabian Sea during Winter Season the more absorbing aerosols are dominating, during Pre-monsoon dust (coarse mode aerosol particles) are more dominating. In winter and pre-monsoon majorly the aerosol forcing is more dominating while during monsoon and post-monsoon season meteorological forcing is more dominating. Over the South Indian Ocean, more or less same types of aerosol (Sea salt) are present. Over the Arabian Sea the Aerosol Indirect Radiative forcing are varying from -5 ± 4.5 W/m² for winter season while in other seasons it is reducing. The results provide observationally constrained estimates of aerosol indirect forcing in the Indian Ocean which can be helpful in evaluating the climate model performance in the context of such complex interactions.

Keywords: aerosol-cloud-precipitation interaction, aerosol-cloud-climate interaction, indirect radiative forcing, climate model

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Authors: Mohamed Abdalla, Ruixue Cheng, Jianyong Zhang

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In pneumatic conveying, the solids are mixed with air or gas. In industries such as coal fired power stations, blast furnaces for iron making, cement and flour processing, the mass flow rate of solids needs to be monitored or controlled. However the current gas-solids two-phase flow measurement techniques are not as accurate as the flow meters available for the single phase flow. One of the problems that the multi-phase flow meters to face is that the flow profiles vary with measurement locations and conditions of pipe routing, bends, elbows and other restriction devices in conveying system as well as conveying velocity and concentration. To measure solids flow rate or concentration with non-even distribution of solids in gas, a uniform spatial sensitivity is required for a multi-phase flow meter. However, there are not many meters inherently have such property. The circular electrostatic meter is a popular choice for gas-solids flow measurement with its high sensitivity to flow, robust construction, low cost for installation and non-intrusive nature. However such meters have the inherent non-uniform spatial sensitivity. This paper first analyses the spatial sensitivity of circular electrostatic meter in general and then by combining the effect of the sensitivity to a single particle and the sensing volume for a given electrode geometry, the paper reveals first time how a circular electrostatic meter responds to a roping flow stream, which is much more complex than what is believed at present. The paper will provide the recent research findings on spatial sensitivity investigation at the University of Tees side based on Finite element analysis using Ansys Fluent software, including time and frequency domain characteristics and the effect of electrode geometry. The simulation results will be compared tothe experimental results obtained on a large scale (14” diameter) rig. The purpose of this research is paving a way to achieve a uniform spatial sensitivity for the circular electrostatic sensor by mean of compensation so as to improve overall accuracy of gas-solids flow measurement.

Keywords: spatial sensitivity, electrostatic sensor, pneumatic conveying, Ansys Fluent software

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Authors: Yasir E. Mohieldeen

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Qatar is one of the most water scarce countries in the World. In 2014, the average per capita rainfall was less than 29 m3/y/ca, while the global average is 6,000 m3/y/ca. However, the per capita water consumption in Qatar is among the highest in the World: more than 500 liters per person per day, whereas the global average is 160 liters per person per day. Since the early 2000s, Qatar has been relying heavily on desalinated water from the Arabian Gulf as the main source of fresh water. In 2009, about 99.9% of the total potable water produced was desalinated. Reliance on desalinated water makes Qatar very vulnerable to water related natural disasters, such as the red-tide phenomenon. Qatar’s strategic water reserve lasts for only 7 days. In case of red-tide outbreak, the country would not be able to desalinate water for days, let alone the months that this disaster would bring about (as it clogs the desalination equipment). The 2008-09 red-tide outbreak, for instance, lasted for more than eight months and forced the closure of desalination plants in the region for weeks. This study aims at identifying favorite conditions for red-tide outbreaks, using satellite data along with in-situ measurements. This identification would allow the prediction of these outbreaks and their hotspots. Prediction and monitoring of outbreaks are crucial to water security in the country, as different measures could be put in place in advance to prevent an outbreak and mitigate its impact if it happened. Red-tide outbreaks are detected using different algorithms for chlorophyll concentration in the Gulf waters. Vegetation indices, such as Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) were used along with Surface Algae Bloom Index (SABI) to detect known outbreaks. MODIS (or Moderate Resolution Imaging Spectroradiometer) bands are used to calculate these indices. A red-tide outbreaks atlas in the Arabian Gulf is being produced. Prediction of red-tide outbreaks ahead of their occurrences would give critical information on possible water-shortage in the country. Detecting known outbreaks in the past few decades and related parameters (e.g. water salinity, water surface temperature, nutrition, sandstorms, … etc) enables the identification of favorite conditions of red-tide outbreak that are key to the prediction of these outbreaks.

Keywords: Arabian Gulf, MODIS, red-tide detection, strategic water reserve, water desalination

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Authors: Alina Muradyan, Lina Babayan, Arsen Nanyan, Gohar Galstyan, Vigen Khachatryan

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We present a photometric method for identifying stars, galaxies and quasars in multi-color surveys, which uses a library of ∼> 65000 color templates for comparison with observed objects. The method aims for extracting the information content of object colors in a statistically correct way, and performs a classification as well as a redshift estimation for galaxies and quasars in a unified approach based on the same probability density functions. For the redshift estimation, we employ an advanced version of the Minimum Error Variance estimator which determines the redshift error from the redshift dependent probability density function itself. The method was originally developed for the Calar Alto Deep Imaging Survey (CADIS), but is now used in a wide variety of survey projects. We checked its performance by spectroscopy of CADIS objects, where the method provides high reliability (6 errors among 151 objects with R < 24), especially for the quasar selection, and redshifts accurate within σz ≈ 0.03 for galaxies and σz ≈ 0.1 for quasars. For an optimization of future survey efforts, a few model surveys are compared, which are designed to use the same total amount of telescope time but different sets of broad-band and medium-band filters. Their performance is investigated by Monte-Carlo simulations as well as by analytic evaluation in terms of classification and redshift estimation. If photon noise were the only error source, broad-band surveys and medium-band surveys should perform equally well, as long as they provide the same spectral coverage. In practice, medium-band surveys show superior performance due to their higher tolerance for calibration errors and cosmic variance. Finally, we discuss the relevance of color calibration and derive important conclusions for the issues of library design and choice of filters. The calibration accuracy poses strong constraints on an accurate classification, which are most critical for surveys with few, broad and deeply exposed filters, but less severe for surveys with many, narrow and less deep filters.

Keywords: VO, ArVO, DFBS, FITS, image processing, data analysis

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Authors: Supriya Gupta, Paresh Chokshi

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Polymer-particle interactions can be effectively utilized to produce composites that possess physicochemical properties superior to that of neat polymer. The incorporation of fillers with dimensions comparable to polymer chain size produces composites with extra-ordinary properties owing to very high surface to volume ratio. The dispersion of nanoparticles is achieved by inducing steric repulsion realized by grafting particles with polymeric chains. A comprehensive understanding of the interparticle interaction between these functionalized nanoparticles plays an important role in the synthesis of a stable polymer nanocomposite. With the focus on incorporation of clay sheets in a polymer matrix, we theoretically construct the polymer mediated interparticle potential for two nanosheets grafted with polymeric chains. The self-consistent field theory (SCFT) is employed to obtain the inhomogeneous composition field under equilibrium. Unlike the continuum models, SCFT is built from the microscopic description taking in to account the molecular interactions contributed by both intra- and inter-chain potentials. We present the results of SCFT calculations of the interaction potential curve for two grafted nanosheets immersed in the matrix of polymeric chains of dissimilar chemistry to that of the grafted chains. The interaction potential is repulsive at short separation and shows depletion attraction for moderate separations induced by high grafting density. It is found that the strength of attraction well can be tuned by altering the compatibility between the grafted and the mobile chains. Further, we construct the interaction potential between two nanosheets grafted with diblock copolymers with one of the blocks being chemically identical to the free polymeric chains. The interplay between the enthalpic interaction between the dissimilar species and the entropy of the free chains gives rise to a rich behavior in interaction potential curve obtained for two separate cases of free chains being chemically similar to either the grafted block or the free block of the grafted diblock chains.

Keywords: clay nanosheets, polymer brush, polymer nanocomposites, self-consistent field theory

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Authors: Eva Slaninova, Diana Cernayova, Zuzana Sedrlova, Katerina Mrazova, Petr Sedlacek, Jana Nebesarova, Stanislav Obruca

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Cyanobacteria are gram-negative prokaryotes belonging to a group of photosynthetic bacteria. In comparison with heterotrophic microorganisms, cyanobacteria utilize atmospheric nitrogen and carbon dioxide without any additional substrates. This ability of these microorganisms could be employed in biotechnology for the production of bioplastics, concretely polyhydroxyalkanoates (PHAs) which are primarily accumulated as a storage material in cells in the form of intracellular granules. In this study, there two cyanobacterial cultures from genera Synechocystis were used, namely Synechocystic sp. PCC 6803 and Synechocystis salina CCALA 192. There were optimized and used several various approaches, including microscopic techniques such as cryo-scanning electron microscopy (Cryo-SEM) and transmission electron microscopy (TEM), and fluorescence lifetime imaging microscopy using Nile red as a fluorescent probe (FLIM). Due to these instrumental techniques, the morphology of intracellular space and surface of cells were characterized. The next group of methods which were employed was spectroscopic techniques such as UV-Vis spectroscopy measured in two modes (turbidimetry and integration sphere) and Fourier transform infrared spectroscopy (FTIR). All these diverse techniques were used for the detection and characterization of pigments (chlorophylls, carotenoids, phycocyanin, etc.) and PHAs, in our case poly (3-hydroxybutyrate) (P3HB). To verify results, gas chromatography (GC) was employed concretely for the determination of the amount of P3HB in biomass. Cyanobacteria were also characterized as polyhydroxybutyrate producers by flow cytometer, which could count cells and at the same time distinguish cells including P3HB and without due to fluorescent probe called BODIPY and live/dead fluorescent probe SYTO Blue. Based on results, P3HB content in cyanobacteria cells was determined, as also the overall fitness of the cells. Acknowledgment: Funding: This study was partly funded by the projectGA19-29651L of the Czech Science Foundation (GACR) and partly funded by the Austrian Science Fund (FWF), project I 4082-B25.

Keywords: cyanobacteria, fluorescent probe, microscopic techniques, poly(3hydroxybutyrate), spectroscopy, chromatography

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Authors: L. Ebralidze, A. Tsertsvadze, D. Berashvili, A. Bakuridze

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Current cancer therapy strategies are based on surgery, radiotherapy and chemotherapy. The problems associated with chemotherapy are one of the biggest challenges for clinical medicine. These include: low specificity, broad spectrum of side effects, toxicity and development of cellular resistance. Therefore, anti-cance drugs need to be develop urgently. Particularly, in order to increase efficiency of anti-cancer drugs and reduce their side effects, scientists work on formulation of nano-drugs. The objective of this study was to develop composition and technology of vincristine nanoparticles using high-molecular carbohydrates of plant origin. Plant polysacharides, particularly, soy bean seed polysaccharides, flaxseed polysaccharides, citrus pectin, gum arabic, sodium alginate were used as objects. Based on biopharmaceutical research, vincristine containing nanoparticle formulations were prepared. High-energy emulsification and solvent evaporation methods were used for preparation of nanosystems. Polysorbat 80, polysorbat 60, sodium dodecyl sulfate, glycerol, polyvinyl alcohol were used in formulation as emulsifying agent and stabilizer of the system. The ratio of API and polysacharides, also the type of the stabilizing and emulsifying agents are very effective on the particle size of the final product. The influence of preparation technology, type and concentration of stabilizing agents on the properties of nanoparticles were evaluated. For the next stage of research, nanosystems were characterized. Physiochemical characterization of nanoparticles: their size, shape, distribution was performed using Atomic force microscope and Scanning electron microscope. The present study explored the possibility of production of NPs using plant polysaccharides. Optimal ratio of active pharmaceutical ingredient and plant polysacharids, the best stabilizer and emulsifying agent was determined. The average range of nanoparticles size and shape was visualized by SEM.

Keywords: nanoparticles, target delivery, natural high molecule carbohydrates, surfactants

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Authors: Amir Gerayeli, Babak Moradi

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The continuously declining oil reservoirs and reservoirs aging have created a huge demand for utilization of Enhanced Oil Recovery (EOR) methods recently. Primary and secondary oil recovery methods have various limitations and are not practical for all reservoirs. Therefore, it is necessary to use chemical methods to improve oil recovery efficiency by reducing oil and water surface tension, increasing sweeping efficiency, and reducing displacer phase viscosity. One of the well-known methods of oil recovery is Alkaline-Surfactant-Polymer (ASP) flooding that shown to have significant impact on enhancing oil recovery. As some of the biggest oil reservoirs including those of Iran’s are fractional reservoirs with substantial amount of trapped oil in their fractures, the use of Alkaline-Surfactant-Polymer (ASP) flooding method is increasingly growing, the method in which the impact of several parameters including type and concentration of the Alkaline, Surfactant, and polymer are particularly important. This study investigated the use of Nano particles to improve Enhanced Oil Recovery (EOR). The study methodology included performing several laboratory tests on drill cores extracted from Karanj Oil field Asmary Formation in Khuzestan, Iran. In the experiments performed, Sodium dodecyl benzenesulfonate (SDBS) and 1-dodecyl-3-methylimidazolium chloride ([C12mim] [Cl])) were used as surfactant, hydrolyzed polyacrylamide (HPAM) and guar gum were used as polymer, Sodium hydroxide (NaOH) as alkaline, and Silicon dioxide (SiO2) and Magnesium oxide (MgO) were used as Nano particles. The experiment findings suggest that water viscosity increased from 1 centipoise to 5 centipoise when hydrolyzed polyacrylamide (HPAM) and guar gum were used as polymer. The surface tension between oil and water was initially measured as 25.808 (mN/m). The optimum surfactant concentration was found to be 500 p, at which the oil and water tension surface was measured to be 2.90 (mN/m) when [C12mim] [Cl] was used, and 3.28 (mN/m) when SDBS was used. The Nano particles concentration ranged from 100 ppm to 1500 ppm in this study. The optimum Nano particle concentration was found to be 1000 ppm for MgO and 500 ppm for SiO2.

Keywords: alkaline-surfactant-polymer, ionic liquids, relative permeability, reduced surface tension, tertiary enhanced oil recovery, wettability change

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Authors: Fatemeh Haghiralsadat, Mohadese Hashemi, Elham Akhoundi Kharanaghi, Mojgan Yazdani, Mahboobe Sharafodini, Omid Javani

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Niosomes are colloidal particles formed from the self-assembly of non-ionic surfactants in aqueous medium resulting in closed bilayer structures. As a consequence of this hydrophilic and hydrophobic structure, niosomes have the capacity to entrap compounds of different solubilities. Niosomes are promising vehicle for drug delivery which protect sensitive drugs and improve the therapeutic index of drugs by restricting their action to target cells. Essential oils are complex mixtures of volatile compounds such as terpenoids, phenol-derived aromatic components that have been used for many biological properties including bactericidal, fungicidal, insecticidal, antioxidant, anti-tyrosinase and other medicinal properties. Encapsulation of essential oils in niosomes can be an attractive method to overcome their limitation such as volatility, easily decomposition by heat, humidity, light, or oxygen. Cuminum cyminum L. (Cumin) is an aromatic plant included in the Apiaceae family and is used to flavor foods, added to fragrances, and for medical preparations which is indigenous to Egypt, the Mediterranean region, Iran and India. The major components of the Cumin oil were reported as cuminaldehyde, γ -terpinene, β-pinene, p-cymene, p-mentha-1, 3-dien-7-al, and p-mentha-1, 4-dien-7-al which provide the antimicrobial and antioxidant activity. The aim of this work was to formulate Cumin essential oil-loaded niosomes to improve water solubility of natural product and evaluate its physico-chemical features and stability. Cumin oil was obtained through steam distillation using a clevenger-type apparatus and GC/MS was applied to identify the main components of the essential oil. Niosomes were prepared by using thin film hydration method and nanoparticles were characterized for particle size, dispersity index, zeta potential, encapsulation efficiency, in vitro release, and morphology.

Keywords: Cuminum cyminum L., Cumin, niosome, essential oil, encapsulation

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Authors: Yexin Qu

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Izafe is a construction typically found in Iranian languages, which is attested already in Old Avestan and Old Persian. The narrow sense of izafe can be described as the linear structure of [NP pt Modifier] with pt as an uninflectable particle or clitic. The history of the Iranian izafe has the following stages: Stage I: Verbless nominal relative clauses, Stage II: Verbless nominal relative clauses with Case Attraction; and Stage III: Narrow sense izafe. Previous works suggest that embedded relative clauses and correlatives in other Indo-European languages might be relevant for the source of the izafe-construction. Stage I, as the precursor of narrow sense izafe, or so-called “prezafe” is not found in branches other than Iranian. Comparable cases have been demonstrated in Vedic, Greek, and some rare cases in Latin. This suggests “prezafe” may date back very early in Indo-European. Izafe-like structures are not attested in branches such as Balto-Slavic and Germanic, but Balto-Slavic definite adjectives and Germanic weak adjectives can be compared to the verbless nominal relative clauses and analyzed as developments of verbless relative clauses parallel to izafe in Indo-Iranian, as are called “parizafe” in this paper. In this paper, the verbless RC is compared with Germanic weak adjectives. The Germanic languages used n-stem derivation to form determined derivatives, which are semantically equivalent to the appositive RC and eventually became weak adjectives. To be more precise, starting from an adjective “X”, the Germanic weak adjective structure is formed as [det X-n], literally “the X”, with the meaning “the X one”, which can be shown to be semantically equivalent to “the one which is X”. In this paper, Stage I suggest that, syntactically, the Germanic verbless relative clauses went through CP to DP relabeling like Iranian, based on the following observations: (1) Germanic relative pronouns (e.g., Gothic saei, Old English se) and determiners (e.g., Gothic sa, Old English se) are both from the *so/to pronominal roots; (2) the semantic equivalence of Germanic weak adjectives and the izafe structure. This may suggest that Germanic may also have had “Prezafe” Stages I and II. In conclusion: “Prezafe” in Stage I may have been a phenomenon of the proto-language, Stage II was the result of independent parallel developments and then each branch had its own strategy.

Keywords: izafe, relative clause, Germanic, Indo-European

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Authors: Thomas Chinedu Aniokete, Gordian Onyebuchukwu Mbah, Michael Daramola

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A sustainable NaOH integrated hydrothermal protocol was developed for the synthesis of waste-derived hydroxy sodalite catalysts for transesterification of waste animal fat (WAF) with a high per cent free fatty acid (FFA) to biodiesel. In this work, hydroxy sodalite catalyst was synthesized from two complex waste materials namely coal fly ash (CFA) and waste industrial brine (WIB). Measured amounts of South African CFA and WIB obtained from a coal mine field were mixed with NaOH solution at different concentrations contained in secured glass vessels equipped with magnetic stirrers and formed consistent slurries after aging condition at 47 oC for 48 h. The slurries were then subjected to hydrothermal treatments at 140 oC for 48 h, washed thoroughly and separated by the action of a centrifuge on the mixture. The resulting catalysts were calcined in a muffle furnace for 2 h at 200 oC and subsequently characterized for different effects using X-ray diffraction (XRD), scanning electron microscopy (SEM), Fourier transform infrared (FT-IR), and Bennett Emmet Teller (BET) adsorption-desorption techniques. The produced animal fat methyl ester (AFME) was analyzed using the gas chromatography-mass spectrometry (GC-MS) method. Results of the investigation indicate profoundly an enhanced catalyst purity, textural property and desired morphology due to the action of NaOH. Similarly, the performance evaluation with respect to catalyst activity reveals a high catalytic conversion efficiency of 98 % of the high FFA WAF to biodiesel under the following reaction conditions; a methanol-to-WAF ratio of 15:1, amount of SOD catalyst of 3 wt % with a stirring speed of 300-500 rpm, a reaction temperature of 60 oC and a reaction time of 8 h. There was a recovered 96 % stable catalyst after reactions and potentially recyclable, thus contributing to the economic savings to the process that had been a major bottleneck to the production of biodiesel. This NaOH route for synthesizing waste-derived hydroxy sodalite (SOD) catalyst is a sustainable and eco-friendly technology that speaks directly to the global quest for renewable-fossil fuel controversy enforcing sustainable development goal 7.

Keywords: coal fly ash, waste industrial brine, waste-derived hydroxy sodalite catalyst, sodium hydroxide, biodiesel, transesterification, biomass conversion

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Authors: Akhila Vasudev, Himanshu Kaushik, Tadikonda Venkata Bharat

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A large number of mine tailings are produced every year as part of the extraction process of phosphates, gold, copper, and other materials. Mine tailings are high in water content and have very slow dewatering behavior. The efficient design of tailings dam and economical disposal of these slurries requires the knowledge of tailings consolidation behavior. The large-strain consolidation theory closely predicts the self-weight consolidation of these slurries as the theory considers the conservation of mass and momentum conservation and considers the hydraulic conductivity as a function of void ratio. Classical laboratory techniques, such as settling column test, seepage consolidation test, etc., are expensive and time-consuming for the estimation of hydraulic conductivity variation with void ratio. Inverse estimation of the constitutive relationships from the measured settlement versus time curves is explored. In this work, inverse analysis based on metaheuristics techniques will be explored for predicting the hydraulic conductivity parameters for mine tailings from the base excess pore water pressure dissipation curve and the initial conditions of the mine tailings. The proposed inverse model uses particle swarm optimization (PSO) algorithm, which is based on the social behavior of animals searching for food sources. The finite-difference numerical solution of the forward analytical model is integrated with the PSO algorithm to solve the inverse problem. The method is tested on synthetic data of base excess pore pressure dissipation curves generated using the finite difference method. The effectiveness of the method is verified using base excess pore pressure dissipation curve obtained from a settling column experiment and further ensured through comparison with available predicted hydraulic conductivity parameters.

Keywords: base excess pore pressure, hydraulic conductivity, large strain consolidation, mine tailings

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Authors: Shahin A. Abdel-Naby, James P. Colgan, Michael S. Pindzola

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A time-dependent close-coupling method is developed to calculate a total, double and triple autoionization rates for hollow atomic ions of four-electron systems. This work was motivated by recent observations of the four-electron Auger process in near K-edge photoionization of C+ ions. The time-dependent close-coupled equations are solved using lattice techniques to obtain a discrete representation of radial wave functions and all operators on a four-dimensional grid with uniform spacing. Initial excited states are obtained by relaxation of the Schrodinger equation in imaginary time using a Schmidt orthogonalization method involving interior subshells. The radial wave function grids are partitioned over the cores on a massively parallel computer, which is essential due to the large memory requirements needed to store the coupled-wave functions and the long run times needed to reach the convergence of the ionization process. Total, double, and triple autoionization rates are obtained by the propagation of the time-dependent close-coupled equations in real-time using integration over bound and continuum single-particle states. These states are generated by matrix diagonalization of one-electron Hamiltonians. The total autoionization rates for each L excited state is found to be slightly above the single autoionization rate for the excited configuration using configuration-average distorted-wave theory. As expected, we find the double and triple autoionization rates to be much smaller than the total autoionization rates. Future work can be extended to study electron-impact triple ionization of atoms or ions. The work was supported in part by grants from the American University of Sharjah and the US Department of Energy. Computational work was carried out at the National Energy Research Scientific Computing Center (NERSC) in Berkeley, California, USA.

Keywords: hollow atoms, autoionization, auger rates, time-dependent close-coupling method

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Authors: S. Ozeri, D. Shmilovitz

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Micro‐Turbine Generators (MTG) are small size power plants that consist of a high speed, gas turbine driving an electrical generator. MTGs may be fueled by either natural gas or kerosene and may also use sustainable and recycled green fuels such as biomass, landfill or digester gas. The typical ratings of MTGs start from 20 kW up to 200 kW. The primary use of MTGs is for backup for sensitive load sites such as hospitals, and they are also considered a feasible power source for Distributed Generation (DG) providing on-site generation in proximity to remote loads. The MTGs have the compressor, the turbine, and the electrical generator mounted on a single shaft. For this reason, the electrical energy is generated at high frequency and is incompatible with the power grid. Therefore, MTGs must contain, in addition, a power conditioning unit to generate an AC voltage at the grid frequency. Presently, this power conditioning unit consists of a rectifier followed by a DC/AC inverter, both rated at the full MTG’s power. The losses of the power conditioning unit account to some 3-5%. Moreover, the full-power processing stage is a bulky and costly piece of equipment that also lowers the overall system reliability. In this study, we propose a new type of power conditioning stage in which only a small fraction of the power is processed. A low power converter is used only to program the rotor current (i.e. the excitation current which is substantially lower). Thus, the MTG's output voltage is shaped to the desired amplitude and frequency by proper programming of the excitation current. The control is realized by causing the rotor current to track the electrical frequency (which is related to the shaft frequency) with a difference that is exactly equal to the line frequency. Since the phasor of the rotation speed and the phasor of the rotor magnetic field are multiplied, the spectrum of the MTG generator voltage contains the sum and the difference components. The desired difference component is at the line frequency (50/60 Hz), whereas the unwanted sum component is at about twice the electrical frequency of the stator. The unwanted high frequency component can be filtered out by a low-pass filter leaving only the low-frequency output. This approach allows elimination of the large power conditioning unit incorporated in conventional MTGs. Instead, a much smaller and cheaper fractional power stage can be used. The proposed technology is also applicable to other high rotation generator sets such as aircraft power units.

Keywords: gas turbine, inverter, power multiplier, distributed generation

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Authors: Xiaoquan Huang, Congcong Li, Tingting Wei, Changcun Bai, Na Liu, Meng Tang

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Silver is often doped on nano-titanium dioxide photocatalysts (Ag-TiO₂) by photodeposition method to improve their utilization of visible-light while increasing the toxicity of TiO₂。 However, it is not known what factors influence this toxicity and how to reduce toxicity while maintaining the maximum catalytic activity. In this study, Ag-TiO₂ photocatalysts were synthesized by the photodeposition method with different silver content (AgC) and photodeposition time (PDT). Characterization and catalytic experiments demonstrated that silver was well assembled on TiO₂ with excellent visible-light catalytic activity, and the size of silver increased with PDT. In vitro, the cell viability of lung epithelial cells A549 and BEAS-2B showed that the higher content and smaller size of silver doping caused higher toxicity. In vivo, Ag-TiO₂ catalysts with lower AgC or larger silver particle size obviously caused less pulmonary pro-inflammatory and pro-fibrosis responses. However, the visible light catalytic activity decreased with the increase in silver size. Therefore, in order to optimize the Ag-TiO₂ photocatalyst with the lowest pulmonary toxicity and highest catalytic performance, response surface methodology (RSM) was further performed to optimize the two independent variables of AgC and PDT. Visible-light catalytic activity was evaluated by the degradation rate of Rhodamine B, the antibacterial property was evaluated by killing log value for Escherichia coli, and cytotoxicity was evaluated by IC50 to BEAS-2B cells. As a result, the RSM model showed that AgC and PDT exhibited an interaction effect on catalytic activity in the quadratic model. AgC was positively correlated with antibacterial activity. Cytotoxicity was proportional to AgC while inversely proportional to PDT. Finally, the optimization values were AgC 3.08 w/w% and PDT 28 min. Under this optimal condition, the relatively high silver proportion ensured the visible-light catalytic and antibacterial activity, while the longer PDT effectively reduced the cytotoxicity. This study is of significance for the safe and efficient application of silver-doped TiO₂ photocatalysts.

Keywords: Ag-doped TiO₂, cytotoxicity, inflammtion, fibrosis, response surface methodology

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Authors: C. Alexandridou, G. N. Angelopoulos, F. A. Coutelieris

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Construction industry in Greece consumes annually more than 25 million tons of natural aggregates originating mainly from quarries. At the same time, more than 2 million tons of construction and demolition waste are deposited every year, usually without control, therefore increasing the environmental impact of this sector. A potential alternative for saving natural resources and minimize landfilling, could be the recycling and re-use of Concrete and Demolition Waste (CDW) in concrete production. Moreover, in order to conform to the European legislation, Greece is obliged to recycle non-hazardous construction and demolition waste to a minimum of 70% by 2020. In this paper characterization of recycled materials - commercially and laboratory produced, coarse and fine, Recycled Concrete Aggregates (RCA) - has been performed. Namely, X-Ray Fluorescence and X-ray diffraction (XRD) analysis were used for chemical and mineralogical analysis respectively. Physical properties such as particle density, water absorption, sand equivalent and resistance to fragmentation were also determined. This study, first time made in Greece, aims at outlining the differences between RCA and natural aggregates and evaluating their possible influence in concrete performance. Results indicate that RCA’s chemical composition is enriched in Si, Al, and alkali oxides compared to natural aggregates. X-ray diffraction (XRD) analyses results indicated the presence of calcite, quartz and minor peaks of mica and feldspars. From all the evaluated physical properties of coarse RCA, only water absorption and resistance to fragmentation seem to have a direct influence on the properties of concrete. Low Sand Equivalent and significantly high water absorption values indicate that fine fractions of RCA cannot be used for concrete production unless further processed. Chemical properties of RCA in terms of water soluble ions are similar to those of natural aggregates. Four different concrete mixtures were produced and examined, replacing natural coarse aggregates with RCA by a ratio of 0%, 25%, 50% and 75% respectively. Results indicate that concrete mixtures containing recycled concrete aggregates have a minor deterioration of their properties (3-9% lower compression strength at 28 days) compared to conventional concrete containing the same cement quantity.

Keywords: chemical and physical characterization, compressive strength, mineralogical analysis, recycled concrete aggregates, waste management

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Authors: I. Tzoka, V. A. Chirayath, A. Brandt, J. Asaadi, Melvin J. Aviles, Stephen Clarke, Stefan Cwik, Michael R. Foley, Cole J. Hamel, Alexey Lyashenko, Michael J. Minot, Mark A. Popecki, Michael E. Stochaj, S. Shin

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Micro-channel plate photo-multiplier tubes (MCP-PMTs) have become ubiquitous and are widely considered potential candidates for next generation High Energy Physics experiments due to their picosecond timing resolution, ability to operate in strong magnetic fields, and low noise rates. A key factor that determines the applicability of MCP-PMTs in their lifetime, especially when they are used in high event rate experiments. We have developed a novel method for the investigation of the aging behavior of an MCP-PMT on an accelerated basis. The method involves exposing a localized region of the MCP-PMT to photons at a high repetition rate. This pixel-based method was inspired by earlier results showing that damage to the photocathode of the MCP-PMT occurs primarily at the site of light exposure and that the surrounding region undergoes minimal damage. One advantage of the pixel-based method is that it allows the dynamics of photo-cathode damage to be studied at multiple locations within the same MCP-PMT under different operating conditions. In this work, we use the pixel-based accelerated lifetime test to investigate the aging behavior of a 20 cm x 20 cm Large Area Picosecond Photo Detector (LAPPD) manufactured by INCOM Inc. at multiple locations within the same device under different operating conditions. We compare the aging behavior of the MCP-PMT obtained from the first lifetime test conducted under high gain conditions to the lifetime obtained at a different gain. Through this work, we aim to correlate the lifetime of the MCP-PMT and the rate of ion feedback, which is a function of the gain of each MCP, and which can also vary from point to point across a large area (400 $cm^2$) MCP. The tests were made possible by the uniqueness of the LAPPD design, which allows independent control of the gain of the chevron stacked MCPs. We will further discuss the implications of our results for optimizing the operating conditions of the detector when used in high event rate experiments.

Keywords: electron multipliers (vacuum), LAPPD, lifetime, micro-channel plate photo-multipliers tubes, photoemission, time-of-flight

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Authors: Evan Lowhorn, Rocio Alba-Flores

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The purpose of this work is to develop a method for classifying hand signals and using the output in a drone control algorithm. To achieve this, methods based on Convolutional Neural Networks (CNN) were applied. CNN's are a subset of deep learning, which allows grid-like inputs to be processed and passed through a neural network to be trained for classification. This type of neural network allows for classification via imaging, which is less intrusive than previous methods using biosensors, such as EMG sensors. Classification CNN's operate purely from the pixel values in an image; therefore they can be used without additional exteroceptive sensors. A development bench was constructed using a desktop computer connected to a high-definition webcam mounted on a scissor arm. This allowed the camera to be pointed downwards at the desk to provide a constant solid background for the dataset and a clear detection area for the user. A MATLAB script was created to automate dataset image capture at the development bench and save the images to the desktop. This allowed the user to create their own dataset of 12,000 images within three hours. These images were evenly distributed among seven classes. The defined classes include forward, backward, left, right, idle, and land. The drone has a popular flip function which was also included as an additional class. To simplify control, the corresponding hand signals chosen were the numerical hand signs for one through five for movements, a fist for land, and the universal “ok” sign for the flip command. Transfer learning with PyTorch (Python) was performed using a pre-trained 18-layer residual learning network (ResNet-18) to retrain the network for custom classification. An algorithm was created to interpret the classification and send encoded messages to a Ryze Tello drone over its 2.4 GHz Wi-Fi connection. The drone’s movements were performed in half-meter distance increments at a constant speed. When combined with the drone control algorithm, the classification performed as desired with negligible latency when compared to the delay in the drone’s movement commands.

Keywords: classification, computer vision, convolutional neural networks, drone control

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Authors: Hassan Qandil

Abstract:

Using a statistical algorithm incorporated in MATLAB, four types of non-imaging Fresnel lenses are designed; spot-flat, linear-flat, dome-shaped and semi-cylindrical-shaped. The optimization employs a statistical ray-tracing methodology of the incident light, mainly considering effects of chromatic aberration, varying focal lengths, solar inclination and azimuth angles, lens and receiver apertures, and the optimum number of prism grooves. While adopting an equal-groove-width assumption of the Poly-methyl-methacrylate (PMMA) prisms, the main target is to maximize the ray intensity on the receiver’s aperture and therefore achieving higher values of heat flux. The algorithm outputs prism angles and 2D sketches. 3D drawings are then generated via AutoCAD and linked to COMSOL Multiphysics software to simulate the lenses under solar ray conditions, which provides optical and thermal analysis at both the lens’ and the receiver’s apertures while setting conditions as per the Dallas-TX weather data. Once the lenses’ characterization is finalized, receivers are designed based on its optimized aperture size. Several cavity shapes; including triangular, arc-shaped and trapezoidal, are tested while coupled with a variety of receiver materials, working fluids, heat transfer mechanisms, and enclosure designs. A vacuum-reflective enclosure is also simulated for an enhanced thermal absorption efficiency. Each receiver type is simulated via COMSOL while coupled with the optimized lens. A lab-scale prototype for the optimum lens-receiver configuration is then fabricated for experimental evaluation. Application-based testing is also performed for the selected configuration, including that of a photovoltaic-thermal cogeneration system and solar furnace system. Finally, some future research work is pointed out, including the coupling of the collector-receiver system with an end-user power generator, and the use of a multi-layered genetic algorithm for comparative studies.

Keywords: COMSOL, concentrator, energy, fresnel, optics, renewable, solar

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Authors: Kinza Qadeer, Muhammad Abdul Qyyum, Moonyong Lee

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Natural gas has become an attractive energy source in comparison with other fossil fuels because of its lower CO₂ and other air pollutant emissions. Therefore, compared to the demand for coal and oil, that for natural gas is increasing rapidly world-wide. The transportation of natural gas over long distances as a liquid (LNG) preferable for several reasons, including economic, technical, political, and safety factors. However, LNG production is an energy-intensive process due to the tremendous amount of power requirements for compression of refrigerants, which provide sufficient cold energy to liquefy natural gas. Therefore, one of the major issues in the LNG industry is to improve the energy efficiency of existing LNG processes through a cost-effective approach that is 'optimization'. In this context, a bio-inspired Krill-herd (KH) step-up approach was examined to enhance the energy efficiency of a single mixed refrigerant (SMR) natural gas liquefaction (LNG) process, which is considered as a most promising candidate for offshore LNG production (FPSO). The optimal design of a natural gas liquefaction processes involves multivariable non-linear thermodynamic interactions, which lead to exergy destruction and contribute to process irreversibility. As key decision variables, the optimal values of mixed refrigerant flow rates and process operating pressures were determined based on the herding behavior of krill individuals corresponding to the minimum energy consumption for LNG production. To perform the rigorous process analysis, the SMR process was simulated in Aspen Hysys® software and the resulting model was connected with the Krill-herd approach coded in MATLAB. The optimal operating conditions found by the proposed approach significantly reduced the overall energy consumption of the SMR process by ≤ 22.5% and also improved the coefficient of performance in comparison with the base case. The proposed approach was also compared with other well-proven optimization algorithms, such as genetic and particle swarm optimization algorithms, and was found to exhibit a superior performance over these existing approaches.

Keywords: energy efficiency, Krill-herd, LNG, optimization, single mixed refrigerant

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Authors: Meghdad Payan, Kostas Senetakis, Arman Khoshghalb, Nasser Khalili

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Dynamic properties of soils, especially at the range of very small strains, are of particular interest in geotechnical engineering practice for characterization of the behavior of geo-structures subjected to a variety of stress states. This study reports on the small-strain dynamic properties of sand-silt mixtures with particular emphasis on the effect of non-plastic fines content on the small strain shear modulus (Gmax), Young’s Modulus (Emax), material damping (Ds,min) and Poisson’s Ratio (v). Several clean sands with a wide range of grain size characteristics and particle shape are mixed with variable percentages of a silica non-plastic silt as fines content. Prepared specimens of sand-silt mixtures at different initial void ratios are subjected to sequential torsional and flexural resonant column tests with elastic dynamic properties measured along an isotropic stress path up to 800 kPa. It is shown that while at low percentages of fines content, there is a significant difference between the dynamic properties of the various samples due to the different characteristics of the sand portion of the mixtures, this variance diminishes as the fines content increases and the soil behavior becomes mainly silt-dominant, rendering no significant influence of sand properties on the elastic dynamic parameters. Indeed, beyond a specific portion of fines content, around 20% to 30% typically denoted as threshold fines content, silt is controlling the behavior of the mixture. Using the experimental results, new expressions for the prediction of small-strain dynamic properties of sand-silt mixtures are developed accounting for the percentage of silt and the characteristics of the sand portion. These expressions are general in nature and are capable of evaluating the elastic dynamic properties of sand-silt mixtures with any types of parent sand in the whole range of silt percentage. The inefficiency of skeleton void ratio concept in the estimation of small-strain stiffness of sand-silt mixtures is also illustrated.

Keywords: damping ratio, Poisson’s ratio, resonant column, sand-silt mixture, shear modulus, Young’s modulus

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Authors: Tulika Malviya, Ritesh Chandra Shukla, Praveen Kumar Tandon

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Traditional methods of synthesis are hazardous for the environment and need nature friendly processes for the treatment of industrial effluents and contaminated water. Use of plant parts for the synthesis provides an efficient alternative method. In this paper, we report an ecofriendly and nonhazardous biobased method to prepare zerovalent iron nanoparticles (ZVINPs) using the liquor of commercially available tea. Tea liquor as the reducing agent has many advantages over other polymers. Unlike other polymers, the polyphenols present in tea extract are nontoxic and water soluble at room temperature. In addition, polyphenols can form complexes with metal ions and thereafter reduce the metals. Third, tea extract contains molecules bearing alcoholic functional groups that can be exploited for reduction as well as stabilization of the nanoparticles. Briefly, iron nanoparticles were prepared by adding 2.0 g of montmorillonite K10 (MMT K10) to 5.0 mL of 0.10 M solution of Fe(NO3)3 to which an equal volume of tea liquor was then added drop wise over 20 min with constant stirring. The color of the mixture changed from whitish yellow to black, indicating the formation of iron nanoparticles. The nanoparticles were adsorbed on montmorillonite K10, which is safe and aids in the separation of hazardous arsenic species simply by filtration. Particle sizes ranging from 59.08±7.81 nm were obtained which is confirmed by using different instrumental analyses like IR, XRD, SEM, and surface area studies. Removal of arsenic was done via batch adsorption method. Solutions of As(III) of different concentrations were prepared by diluting the stock solution of NaAsO2 with doubly distilled water. The required amount of in situ prepared ZVINPs supported on MMT K10 was added to a solution of desired strength of As (III). After the solution had been stirred for the preselected time, the solid mass was filtered. The amount of arsenic [in the form of As (V)] remaining in the filtrate was measured using ion chromatograph. Stirring of contaminated water with zerovalent iron nanoparticles supported on montmorillonite K10 for 30 min resulted in up to 99% removal of arsenic as As (III) from its solution at both high and low pH (2.75 and 11.1). It was also observed that, under similar conditions, montmorillonite K10 alone provided only <10% removal of As(III) from water. Adsorption at low pH with precipitation at higher pH has been proposed for As(III) removal.

Keywords: arsenic removal, montmorillonite K10, tea liquor, zerovalent iron nanoparticles

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Authors: Wei Liu, Shuquan Wang, Yang Gao

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Microgravity Science Experiment Rack (MSER) will be onboard TianHe (TH) spacecraft planned to be launched in 2018. TH is one module of Chinese Space Station. Microgravity Vibration Isolation System (MVIS), which is MSER’s core part, is used to isolate disturbance from TH and provide high-level microgravity for science experiment payload. MVIS is two stage vibration isolation system, consisting of Follow Unit (FU) and Experiment Support Unit (ESU). FU is linked to MSER by umbilical cables, and ESU suspends within FU and without physical connection. The FU’s position and attitude relative to TH is measured by binocular vision measuring system, and the acceleration and angular velocity is measured by accelerometers and gyroscopes. Air-jet thrusters are used to generate force and moment to control FU’s motion. Measurement module on ESU contains a set of Position-Sense-Detectors (PSD) sensing the ESU’s position and attitude relative to FU, accelerometers and gyroscopes sensing ESU’s acceleration and angular velocity. Electro-magnetic actuators are used to control ESU’s motion. Firstly, the linearized equations of FU’s motion relative to TH and ESU’s motion relative to FU are derived, laying the foundation for control system design and simulation analysis. Subsequently, two control schemes are proposed. One control scheme is that ESU tracks FU and FU tracks TH, shorten as E-F-T. The other one is that FU tracks ESU and ESU tracks TH, shorten as F-E-T. In addition, motion spaces are constrained within ±15 mm、±2° between FU and ESU, and within ±300 mm between FU and TH or between ESU and TH. A Proportional-Integrate-Differentiate (PID) controller is designed to control FU’s position and attitude. ESU’s controller includes an acceleration feedback loop and a relative position feedback loop. A Proportional-Integrate (PI) controller is designed in the acceleration feedback loop to reduce the ESU’s acceleration level, and a PID controller in the relative position feedback loop is used to avoid collision. Finally, simulations of E-F-T and F-E-T are performed considering variety uncertainties, disturbances and motion space constrains. The simulation results of E-T-H showed that control performance was from 0 to -20 dB for vibration frequency from 0.01 to 0.1 Hz, and vibration was attenuated 40 dB per ten octave above 0.1Hz. The simulation results of T-E-H showed that vibration was attenuated 20 dB per ten octave at the beginning of 0.01Hz.

Keywords: microgravity science experiment rack, microgravity vibration isolation system, PID control, vibration isolation performance

Procedia PDF Downloads 156

Authors: Kottaridi Klimentia, Demopoulos Vasilis, Sidiropoulos Anastasios, Ihara Diego, Nikolaidis Vasileios, Antonopoulos Dimitrios

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Aflatoxins are highly poisonous and carcinogenic compounds produced by species of the genus Aspergillus spp. that can infect a variety of agricultural foods, including dried figs. Biological and environmental factors, such as population, pathogenicity, and aflatoxinogenic capacity of the strains, topography, soil, and climate parameters of the fig orchards, are believed to have a strong effect on aflatoxin levels. Existing methods for aflatoxin detection and measurement, such as high performance liquid chromatography (HPLC), and enzyme-linked immunosorbent assay (ELISA), can provide accurate results, but the procedures are usually time-consuming, sample-destructive, and expensive. Predicting aflatoxin levels prior to crop harvest is useful for minimizing the health and financial impact of a contaminated crop. Consequently, there is interest in developing a tool that predicts aflatoxin levels based on topography and soil analysis data of fig orchards. This paper describes the development of a risk assessment tool for the contamination of aflatoxin on dried figs, based on the location and altitude of the fig orchards, the population of the fungus Aspergillus spp. in the soil, and soil parameters such as pH, saturation percentage (SP), electrical conductivity (EC), organic matter, particle size analysis (sand, silt, clay), the concentration of the exchangeable cations (Ca, Mg, K, Na), extractable P, and trace of elements (B, Fe, Mn, Zn and Cu), by employing machine learning methods. In particular, our proposed method integrates three machine learning techniques, i.e., dimensionality reduction on the original dataset (principal component analysis), metric learning (Mahalanobis metric for clustering), and k-nearest neighbors learning algorithm (KNN), into an enhanced model, with mean performance equal to 85% by terms of the Pearson correlation coefficient (PCC) between observed and predicted values.

Keywords: aflatoxins, Aspergillus spp., dried figs, k-nearest neighbors, machine learning, prediction

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Authors: Omar Khan, Shana Krstevska, Edwin George, Veronica Gorden, Fen Bao, Christina Caon, NP-C, Carla Santiago, Imad Zak, Navid Seraji-Bozorgzad

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Objective: To quantify cellular injury in the substantia nigra (SN) in patients with Parkinson's disease (PD) and to examine the effect of rasagiline of tissue injury in the SN in patients with PD. Background: N-acetylaspartate (NAA) quantified with MRS is a reliable marker of neuronal metabolic function. Fractional anisotropy (FA) and mean diffusivity (MD) obtained with DTI, characterize tissue alignment and integrity. Rasagline, has been shown to exert anti-apototic effect. We applied these advanced MRI techniques to examine: (i) the effect of rasagiline on cellular injury and metabolism in patients with early PD, and (ii) longitudinal changes seen over time in PD. Methods: We conducted a prospective longitudinal study in patients with mild PD, naive to dopaminergic treatment. The imaging protocol included multi-voxel proton-MRS and DTI of the SN, acquired on a 3T scanner. Scans were performed at baseline and month 3, during which the patient was on no treatment. At that point, rasagiline 1 mg orally daily was initiated and MRI scans are were obtained at 6 and 12 months after starting rasagiline. The primary objective was to compare changes during the 3-month period of “no treatment” to the changes observed “on treatment” with rasagiline at month 12. Age-matched healthy controls were also imaged. Image analysis was performed blinded to treatment allocation and period. Results: 25 patients were enrolled in this study. Compared to the period of “no treatment”, there was significant increase in the NAA “on treatment” period (-3.04 % vs +10.95 %, p= 0.0006). Compared to the period of “no treatment”, there was significant increase in following 12 month in the FA “on treatment” (-4.8% vs +15.3%, p<0.0001). The MD increased during “no treatment” and decreased in “on treatment” (+2.8% vs -7.5%, p=0.0056). Further analysis and clinical correlation are ongoing. Conclusions: Advanced MRI techniques quantifying cellular injury in the SN in PD is a feasible approach to investigate dopaminergic neuronal injury and could be developed as an outcome in exploratory studies. Rasagiline appears to have a stabilizing effect on dopaminergic cell loss and metabolism in the SN in PD, that warrants further investigation in long-term studies.

Keywords: substantia nigra, Parkinson's disease, MRI, neuronal loss, biomarker

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Authors: Laura Vitola, Diana Bajare, Genadijs Sahmenko, Girts Bumanis

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About 8 % of CO2 emission in the world is produced by concrete industry therefore replacement of cement in concrete composition by additives with pozzolanic activity would give a significant impact on the environment. Material which contains silica SiO2 or amorphous silica SiO2 together with aluminum dioxide Al2O3 is called pozzolana type additives in the concrete industry. Pozzolana additives are possible to obtain from recycling industry and different production by-products such as processed bulb boric silicate (DRL type) and lead (LB type) glass, coal combustion bottom ash, utilized brick pieces and biomass ash, thus solving utilization problem which is so important in the world, as well as practically using materials which previously were considered as unusable. In the literature, there is no summarized method which could be used for quick waste-product pozzolana activity evaluation without the performance of wide researches related to the production of innumerable concrete contents and samples in the literature. Besides it is important to understand which parameters should be predicted to characterize the efficiency of waste-products. Simple methods of pozzolana activity increase for different types of waste-products are also determined. The aim of this study is to evaluate effectiveness of the different types of waste materials and industrial by-products (coal combustion bottom ash, biomass ash, waste glass, waste kaolin and calcined illite clays), and determine which parameters have the greatest impact on pozzolanic activity. By using materials, which previously were considered as unusable and landfilled, in concrete industry basic utilization problems will be partially solved. The optimal methods for treatment of waste materials and industrial by–products were detected with the purpose to increase their pozzolanic activity and produce substitutes for cement in the concrete industry. Usage of mentioned pozzolanic allows us to replace of necessary cement amount till 20% without reducing the compressive strength of concrete.

Keywords: cement substitutes, micro and nano fillers, pozzolanic properties, specific surface area, particle size, waste products

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Authors: Sneha Singh, Abhimanyu Dev, Vinod Nigam

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The major issue which decides the impending use of gold nanoparticles (AuNPs) in nanobiotechnological applications is their particle size and stability. Often the AuNPs obtained biomimetically are considered useless owing to their instability in the aqueous medium and thereby limiting the widespread acceptance of this facile green synthesis procedure. So, the use of nontoxic surfactants is warranted to stabilize the biogenic nanoparticles (NPs). But does the surfactant only play a role in stabilizing by being adsorbed to the NPs surface or can it have any other significant contribution in synthesis process and controlling their size as well as shape? Keeping this idea in mind, AuNPs were synthesized by using surfactant treated (lechate) and untreated (cell lysate supernatant) Bacillus licheniformis cell extract. The cell extracts mediated reduction of chloroauric acid (HAuCl 4) in the presence of non-ionic surfactant, Tween 20 (TW20), and its effect on the AuNPs stability was studied. Interestingly, the surfactant used in the study served as potential alternative to harvest cellular enzymes involved in bioreduction process in a hassle free condition. The surfactants ability to solubilize/leach membrane proteins and simultaneously stabilizing the AuNPs could have advantage from process point of view as it will reduce the time and economics involve in the nanofabrication of biogenic NPs. The synthesis was substantiated with UV-Vis spectroscopy, Dynamic light scattering study, FTIR spectroscopy, and Transmission electron microscopy. The Zeta potential of AuNPs solutions was measured routinely to corroborate the stability observations recorded visually. Highly stable, ultra-small AuNPs of 2.6 nm size were obtained from the study. Further, the biological efficacy of the obtained AuNPs as potential antibacterial agent was evaluated against Bacilllus subtilis, Pseudomonas aeruginosa, and Escherichia coli by observing the zone of inhibition. This potential of AuNPs of size < 3 nm as antibacterial agent could pave way for development of new antimicrobials and overcoming the problems of antibiotics resistance

Keywords: antibacterial, bioreduction, nanoparticles, surfactant

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