Search results for: spectral lithology

Authors: Neha Bhattacharyya, Soumendra Singh, Amrita Banerjee, Ria Ghosh, Oindrila Sinha, Nairit Das, Rajkumar Gayen, Somya Subhra Pal, Sahely Ganguly, Tanmoy Dasgupta, Tanusree Dasgupta, Pulak Mondal, Aniruddha Adhikari, Sharmila Sarkar, Debasish Bhattacharyya, Asim Kumar Mallick, Om Prakash Singh, Samir Kumar Pal

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Background: We aim to develop an integrated device comprised of single-probe EEG and CCD-based motion sensors for a more objective measure of Attention-deficit Hyperactivity Disorder (ADHD). While the integrated device (MAHD) relies on the EEG signal (spectral density of beta wave) for the assessment of attention during a given structured task (painting three segments of a circle using three different colors, namely red, green and blue), the CCD sensor depicts movement pattern of the subjects engaged in a continuous performance task (CPT). A statistical analysis of the attention and movement patterns was performed, and the accuracy of the completed tasks was analysed using indigenously developed software. The device with the embedded software, called MAHD, is intended to improve certainty with criterion E (i.e. whether symptoms are better explained by another condition). Methods: We have used the EEG signal from a single-channel dry sensor placed on the frontal lobe of the head of the subjects (3-5 years old pre-schoolers). During the painting of three segments of a circle using three distinct colors (red, green, and blue), absolute power for delta and beta EEG waves from the subjects are found to be correlated with relaxation and attention/cognitive load conditions. While the relaxation condition of the subject hints at hyperactivity, a more direct CCD-based motion sensor is used to track the physical movement of the subject engaged in a continuous performance task (CPT) i.e., separation of the various colored balls from one table to another. We have used our indigenously developed software for the statistical analysis to derive a scale for the objective assessment of ADHD. We have also compared our scale with clinical ADHD evaluation. Results: In a limited clinical trial with preliminary statistical analysis, we have found a significant correlation between the objective assessment of the ADHD subjects with that of the clinician’s conventional evaluation. Conclusion: MAHD, the integrated device, is supposed to be an auxiliary tool to improve the accuracy of ADHD diagnosis by supporting greater criterion E certainty.

Keywords: ADHD, CPT, EEG signal, motion sensor, psychometric test

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Authors: Sakeena Naikwadi, K. Jagaluraiah Sannapapamma

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Vetiveria zizanioides is an aromatic grass and traditionally been used in aromatherapy and ayurvedic medicine. Vetiver root is multi-functional biopolymer and has highly aromatic, antimicrobial, UV blocking, antioxidant properties suitable for textile finishing. The vetiver root (Gulabi) powder of different concentration (2, 4, 6,8 percent) were extracted by aqueous and solvent methods subjected to bioassay for antimicrobial efficiency and GCMS spectral analysis. The organic cotton fabric was finished with vetiver root extract (8 percent) by exhaust and pad dry cure methods. The finished fabric was assessed for functional properties viz., UV protective factor, antimicrobial efficiency and aroma intensity. The results revealed that Ethanol extraction showed a greater zone of inhibition compared to aqueous extract in root powder. Among the concentrations, 8 percent root extract in ethanol showed a greater zone of inhibition against gram-positive organism S. aureus and gram-negative organism E. coli. The major compounds present in vetiver root extracts were diethyl pathalate with greater percentage (87.73 %) followed by 7- Isopropyl dimethyl carboxylic acid (4.05 %), 2-butanone 4-trimethyle cyclohexen (1.21 %), phenanthrene carboxylic acid (1.03 %), naphthalene pentanoic acid (0.99 %), 1-phenanthrene carboxylic acid and 1 cyclohexenone 2-methyl oxobuty (0.89 %). The sample finished by pad dry cure method exhibited better UV protection even after 10th wash as compared to exhaust method. Vetiver extract treated samples exhibited maximum zone of inhibition against S. aureus than the E. coli organism. The vetiver root extract treated organic cotton fabric through pad dry cure method possessed good antimicrobial activity against S. aureus and E. coli even after 20th washes compared to vetiver root extract treated by exhaust method. The olfactory analysis was carried out by 30 panels of members and opined that vetiver root extract treated fabric has very good and pleasant aroma with better tactile properties that provide cooling, soothing effect and enhances the mood of the wearer. Vetiver root extract finished organic cotton fabric possessed aroma, antimicrobial and UV properties which are aptly suitable for medical and healthcare textiles viz., wound dressing, bandage gauze, surgical cloths, baby diapers and sanitary napkins. It can be used as after finishing agent for variegated garments and made-ups and can be replaced with commercial after finishing agents.

Keywords: antimicrobial, olfactory analysis, UV protection factor, vetiver root extract

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Authors: A. D. Rao, Sachiko Mohanty

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The Internal Waves (IWs) are generated by the flow of barotropic tide over the rapidly varying and steep topographic features like continental shelf slope, subsurface ridges, and the seamounts, etc. The IWs of the tidal frequency are generally known as internal tides. These waves have a significant influence on the vertical density and hence causes mixing in the region. Such waves are also important in submarine acoustics, underwater navigation, offshore structures, ocean mixing and biogeochemical processes, etc. over the shelf-slope region. The seasonal variability of internal tides in the Bay of Bengal with special emphasis on its energetics is examined by using three-dimensional MITgcm model. The numerical simulations are performed for different periods covering August-September, 2013; November-December, 2013 and March-April, 2014 representing monsoon, post-monsoon and pre-monsoon seasons respectively during which high temporal resolution in-situ data sets are available. The model is initially validated through the spectral estimates of density and the baroclinic velocities. From the estimates, it is inferred that the internal tides associated with semi-diurnal frequency are more dominant in both observations and model simulations for November-December and March-April. However, in August, the estimate is found to be maximum near-inertial frequency at all the available depths. The observed vertical structure of the baroclinic velocities and its magnitude are found to be well captured by the model. EOF analysis is performed to decompose the zonal and meridional baroclinic tidal currents into different vertical modes. The analysis suggests that about 70-80% of the total variance comes from Mode-1 semi-diurnal internal tide in both observations as well as in the model simulations. The first three modes are sufficient to describe most of the variability for semidiurnal internal tides, as they represent 90-95% of the total variance for all the seasons. The phase speed, group speed, and wavelength are found to be maximum for post-monsoon season compared to other two seasons. The model simulation suggests that the internal tide is generated all along the shelf-slope regions and propagate away from the generation sites in all the months. The model simulated energy dissipation rate infers that its maximum occurs at the generation sites and hence the local mixing due to internal tide is maximum at these sites. The spatial distribution of available potential energy is found to be maximum in November (20kg/m²) in northern BoB and minimum in August (14kg/m²). The detailed energy budget calculation are made for all the seasons and results are analysed.

Keywords: available potential energy, baroclinic energy flux, internal tides, Bay of Bengal

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Authors: Linta Rose, Prasad K. Bhaskaran

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Water-level information along the coast is very important for disaster management, navigation, planning shoreline management, coastal engineering and protection works, port and harbour activities, and for a better understanding of near-shore ocean dynamics. The water-level variation along a coast attributes from various factors like astronomical tides, meteorological and hydrological forcing. The study area is the Head Bay of Bengal which is highly vulnerable to flooding events caused by monsoons, cyclones and sea-level rise. The study aims to explore the extent to which wind and surface pressure can influence water-level elevation, in view of the low-lying topography of the coastal zones in the region. The ADCIRC hydrodynamic model has been customized for the Head Bay of Bengal, discretized using flexible finite elements and validated against tide gauge observations. Monthly mean climatological wind and mean sea level pressure fields of ERA Interim reanalysis data was used as input forcing to simulate water-level variation in the Head Bay of Bengal, in addition to tidal forcing. The output water-level was compared against that produced using tidal forcing alone, so as to quantify the contribution of meteorological forcing to water-level. The average contribution of meteorological fields to water-level in January is 5.5% at a deep-water location and 13.3% at a coastal location. During the month of July, when the monsoon winds are strongest in this region, this increases to 10.7% and 43.1% respectively at the deep-water and coastal locations. The model output was tested by varying the input conditions of the meteorological fields in an attempt to quantify the relative significance of wind speed and wind direction on water-level. Under uniform wind conditions, the results showed a higher contribution of meteorological fields for south-west winds than north-east winds, when the wind speed was higher. A comparison of the spectral characteristics of output water-level with that generated due to tidal forcing alone showed additional modes with seasonal and annual signatures. Moreover, non-linear monthly mode was found to be weaker than during tidal simulation, all of which point out that meteorological fields do not cause much effect on the water-level at periods less than a day and that it induces non-linear interactions between existing modes of oscillations. The study signifies the role of meteorological forcing under fair weather conditions and points out that a combination of multiple forcing fields including tides, wind, atmospheric pressure, waves, precipitation and river discharge is essential for efficient and effective forecast modelling, especially during extreme weather events.

Keywords: ADCIRC, head Bay of Bengal, mean sea level pressure, meteorological forcing, water-level, wind

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Authors: Pantea Salehizadeh, Martin P. Bucknall, Robert Driscoll, Jayashree Arcot, George Srzednicki

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Banana is one of the most important crops produced in large quantities in tropical and sub-tropical countries. Of the total plant material grown, approximately 40% is considered waste and left in the field to decay. This practice allows fungal diseases such as Sigatoka Leaf Spot to develop, limiting plant growth and spreading spores in the air that can cause respiratory problems in the surrounding population. The pseudostem is considered a waste residue of production (60 to 80 tonnes/ha/year), although it is a good source of dietary fiber and volatile organic compounds (VOC’s). Strategies to process banana pseudostem into palatable, nutritious and marketable food materials could provide significant social and economic benefits. Extraction of VOC’s with desirable odor from dried and fresh pseudostem could improve the smell of products from the confectionary and bakery industries. Incorporation of banana pseudostem flour into bakery products could provide cost savings and improve nutritional value. The aim of this study was to determine the effects of drying methods and different banana species on the profile of volatile aroma compounds in dried banana pseudostem. The banana species analyzed were Musa acuminata and Musa balbisiana. Fresh banana pseudostem samples were processed by either freeze-drying (FD) or heat pump drying (HPD). The extraction of VOC’s was performed at ambient temperature using vacuum distillation and the resulting, mostly aqueous, distillates were analyzed using headspace solid phase microextraction (SPME) gas chromatography – mass spectrometry (GC-MS). Optimal SPME adsorption conditions were 50 °C for 60 min using a Supelco 65 μm PDMS/DVB Stableflex fiber1. Compounds were identified by comparison of their electron impact mass spectra with those from the Wiley 9 / NIST 2011 combined mass spectral library. The results showed that the two species have notably different VOC profiles. Both species contained VOC’s that have been established in literature to have pleasant appetizing aromas. These included l-Menthone, D-Limonene, trans-linlool oxide, 1-Nonanol, CIS 6 Nonen-1ol, 2,6 Nonadien-1-ol, Benzenemethanol, 4-methyl, 1-Butanol, 3-methyl, hexanal, 1-Propanol, 2-methyl- acid، 2-Methyl-2-butanol. Results show banana pseudostem VOC’s are better preserved by FD than by HPD. This study is still in progress and should lead to the optimization of processing techniques that would promote the utilization of banana pseudostem in the food industry.

Keywords: heat pump drying, freeze drying, SPME, vacuum distillation, VOC analysis

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Authors: Shyan-Lung Lin, Cheng-Yi Huang, Tung-Yi Lin

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Physical fitness is the adaptability of the body to physical work and the environment, and is generally known to include cardiopulmonary-fitness, muscular-fitness, body flexibility, and body composition. This paper is aimed to study the ventilatory and cardiovascular activity under various exercise intensities for subjects at distinct ends of cardiopulmonary fitness norm. Three graded upright biking exercises, light, moderate, and vigorous exercise, were designed for subjects at distinct ends of cardiopulmonary fitness norm from their physical education classes. The participants in the experiments were 9, 9, and 11 subjects in the top 20%, middle 20%, and bottom 20%, respectively, among all freshmen of the Feng Chia University in the academic year of 2015. All participants were requested to perform 5 minutes of upright biking exercise to attain 50%, 65%, and 85% of their maximum heart rate (HRmax) during the light, moderate, and vigorous exercise experiment, respectively, and 5 minutes of recovery following each graded exercise. The cardiovascular and ventilatory signals, including breathing frequency (f), tidal volume (VT), heart rate (HR), mean arterial pressure (MAP), and ECG signals were recorded during rest, exercise, and recovery periods. The physiological signals of three groups were analyzed based on their recovery, recovery rate, and percentage variation from rest. Selected time domain parameters, SDNN and RMSSD, were computed and spectral analysis was performed to study the hear rate variability from collected ECG signals. The comparison studies were performed to examine the correlations between physical fitness norm and cardio-pulmonary signals during graded exercises and exercise recovery. No significant difference was found among three groups with VT during all levels of exercise intensity and recovery. The top 20% group was found to have better performance in heart recovery (HRR), frequency recovery rate (fRR) and percentage variation from rest (Δf) during the recovery period of vigorous exercise. The top 20% group was also found to achieve lower mean arterial pressure MAP only at rest but showed no significant difference during graded exercises and recovery periods. In time-domain analysis of HRV, the top 20% group again seemed to have better recovery rate and less variation in terms of SDNN during recovery period of light and vigorous exercises. Most assessed frequency domain parameters changed significantly during the experiment (p<0.05, ANOVA). The analysis showed that the top 20% group, in comparison with middle and bottom 20% groups, appeared to have significantly higher TP, LF, HF, and nHF index, while the bottom 20% group showed higher nLF and LF/HF index during rest, three graded levels of exercises, and their recovery periods.

Keywords: physical fitness, cardio-pulmonary signals, graded exercise, exercise recovery

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Authors: Ping-Hsiung Wang, Kuo-Chun Chang

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There has been a common trend worldwide in the seismic design and evaluation of bridges towards the performance-based method where the lateral displacement or the displacement ductility of bridge column is regarded as an important indicator for performance assessment. However, the seismic response of a bridge to an earthquake is a combined result of cyclic displacements and accumulated energy dissipation, causing damage to the bridge, and hence the lateral displacement (ductility) alone is insufficient to tell its actual seismic performance. This study aims to propose a damage-based seismic design and evaluation method for reinforced concrete bridges on the basis of the newly developed capacity-based inelastic displacement spectra. The capacity-based inelastic displacement spectra that comprise an inelastic displacement ratio spectrum and a corresponding damage state spectrum was constructed by using a series of nonlinear time history analyses and a versatile, smooth hysteresis model. The smooth model could take into account the effects of various design parameters of RC bridge columns and correlates the column’s strength deterioration with the Park and Ang’s damage index. It was proved that the damage index not only can be used to accurately predict the onset of strength deterioration, but also can be a good indicator for assessing the actual visible damage condition of column regardless of its loading history (i.e., similar damage index corresponds to similar actual damage condition for the same designed columns subjected to very different cyclic loading protocols as well as earthquake loading), providing a better insight into the seismic performance of bridges. Besides, the computed spectra show that the inelastic displacement ratio for far-field ground motions approximately conforms to the equal displacement rule when structural period is larger than around 0.8 s, but that for near-fault ground motions departs from the rule in the whole considered spectral regions. Furthermore, the near-fault ground motions would lead to significantly greater inelastic displacement ratio and damage index than far-field ground motions and most of the practical design scenarios cannot survive the considered near-fault ground motion when the strength reduction factor of bridge is not less than 5.0. Finally, the spectrum formula is presented as a function of structural period, strength reduction factor, and various column design parameters for far-field and near-fault ground motions by means of the regression analysis of the computed spectra. And based on the developed spectrum formula, a design example of a bridge is presented to illustrate the proposed damage-based seismic design and evaluation method where the damage state of the bridge is used as the performance objective.

Keywords: damage index, far-field, near-fault, reinforced concrete bridge, seismic design and evaluation

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Authors: Miguel Contreras, David Long, Will Bachman

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

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

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Authors: Khalid Omari, Rene Chenier, Enrique Blondel, Ryan Ahola

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Northern Canadian coasts have vulnerable and very dynamic intertidal zones with very high tides occurring in several areas. The impact of climate change presents challenges not only for maintaining this biodiversity but also for navigation safety adaptation due to the high sediment mobility in these coastal areas. Thus, frequent mapping of shorelines and intertidal changes is of high importance. To help in quantifying the changes in these fragile ecosystems, remote sensing provides practical monitoring tools at local and regional scales. Traditional methods based on high-resolution optical sensors are often used to map intertidal areas by benefiting of the spectral response contrast of intertidal classes in visible, near and mid-infrared bands. Tidal areas are highly reflective in visible bands mainly because of the presence of fine sand deposits. However, getting a cloud-free optical data that coincide with low tides in intertidal zones in northern regions is very difficult. Alternatively, the all-weather capability and daylight-independence of the microwave remote sensing using synthetic aperture radar (SAR) can offer valuable geophysical parameters with a high frequency revisit over intertidal zones. Multi-polarization SAR parameters have been used successfully in mapping intertidal zones using incoherence target decomposition. Moreover, the crustal displacements caused by ocean tide loading may reach several centimeters that can be detected and quantified across differential interferometric synthetic aperture radar (DInSAR). Soil moisture change has a significant impact on both the coherence and the backscatter. For instance, increases in the backscatter intensity associated with low coherence is an indicator for abrupt surface changes. In this research, we present primary results obtained following our investigation of the potential of the fully polarimetric Radarsat-2 data for mapping an inter-tidal zone located on Tasiujaq on the south-west shore of Ungava Bay, Quebec. Using the repeat pass cycle of Radarsat-2, multiple seasonal fine quad (FQ14W) images are acquired over the site between 2016 and 2018. Only 8 images corresponding to low tide conditions are selected and used to build an interferometric stack of data. The observed displacements along the line of sight generated using HH and VV polarization are compared with the changes noticed using the Freeman Durden polarimetric decomposition and Touzi degree of polarization extrema. Results show the consistency of both approaches in their ability to monitor the changes in intertidal zones.

Keywords: SAR, degree of polarization, DInSAR, Freeman-Durden, polarimetry, Radarsat-2

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Authors: Xiaoyun Hui, Fiona Gentle, Clemens Engelke, Margaret C. Graham

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Although past work has shown that phosphorus (P), an important nutrient, may form complexes with aqueous humic substances (HS), the principal component of natural organic matter, the nature of such interactions is poorly understood. Humic complexation may not only enhance P concentrations but it may change its bioavailability within such waters and, in addition, influence its transport within catchment settings. This project is examining the relationships and associations of P, HS, and iron (Fe) in Loch Meadie, Sutherland, North Scotland, a mesohumic freshwater loch which has been assessed as reference condition with respect to P. The aim is to identify characteristic spectroscopic parameters which can enhance the performance of the model currently used to predict reference condition TP levels for highly-coloured Scottish lochs under the Water Framework Directive. In addition to Loch Meadie, samples from other reference condition lochs in north Scotland and Shetland were analysed. By including different types of reference condition lochs (clear water, mesohumic and polyhumic water) this allowed the relationship between total phosphorus (TP) and HS to be more fully explored. The pH, [TP], [Fe], UV/Vis absorbance/spectra, [TOC] and [DOC] for loch water samples have been obtained using accredited methods. Loch waters were neutral to slightly acidic/alkaline (pH 6-8). [TP] in loch waters were lower than 50 µg L-1, and in Loch Meadie waters were typically <10 µg L-1. [Fe] in loch waters were mainly <0.6 mg L-1, but for some loch water samples, [Fe] were in the range 1.0-1.8 mg L-1and there was a positive correlation with [TOC] (r2=0.61). Lochs were classified as clear water, mesohumic or polyhumic based on water colour. The range of colour values of sampled lochs in each category were 0.2–0.3, 0.2–0.5 and 0.5–0.8 a.u. (10 mm pathlength), respectively. There was also a strong positive correlation between [DOC] and water colour (R2=0.84). The UV/Vis spectra (200-700 nm) for water samples were featureless with only a slight “shoulder” observed in the 270–290 nm region. Ultrafiltration was then used to separate colloidal and truly dissolved components from the loch waters and, since it contained the majority of aqueous P and Fe, the colloidal component was fractionated by gel filtration chromatography method. Gel filtration chromatographic fractionation of the colloids revealed two brown-coloured bands which had distinctive UV/Vis spectral features. The first eluting band had larger and more aromatic HS molecules than the second band, and in addition both P and Fe were primarily associated with the larger, more aromatic HS. This result demonstrated that P was able to form complexes with Fe-rich components of HS, and thus provided a scientific basis for the significant correlation between [Fe] and [TP] that the previous monitoring data of reference condition lochs from Scottish Environment Protection Agency (SEPA) showed. The distinctive features of the HS will be used as the basis for an improved spectroscopic tool.

Keywords: total phosphorus, humic substances, Scottish loch water, WFD model

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Authors: Mohit Kumar

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Natural fractures are classified in two broad categories of joints and faults on the basis of shear movement in the deposited strata. Natural fracture always has high structural relationship with extensional or non-extensional tectonics and sometimes the result is seen in the form of micro cracks. Geological evidences suggest that both large and small-scale fractures help in to analyze the seismic anisotropy which essentially contribute into characterization of petro physical properties behavior associated with directional migration of fluid. We generally question why basement study is much needed as historically it is being treated as non-productive and geoscientist had no interest in exploration of these basement rocks. Basement rock goes under high pressure and temperature, and seems to be highly fractured because of the tectonic stresses that are applied to the formation along with the other geological factors such as depositional trend, internal stress of the rock body, rock rheology, pore fluid and capillary pressure. Sometimes carbonate rocks also plays the role of basement and igneous body e.g basalt deposited over the carbonate rocks and fluid migrate from carbonate to igneous rock due to buoyancy force and adequate permeability generated by fracturing. So in order to analyze the complete petroleum system, FMC (Fluid Migration Characterization) is necessary through fractured media including fracture intensity, orientation and distribution both in basement rock and county rock. Thus good understanding of fractures can lead to project the correct wellbore trajectory or path which passes through potential permeable zone generated through intensified P-T and tectonic stress condition. This paper deals with the analysis of these fracture property such as intensity, orientation and distribution in basement rock as large scale fracture can be interpreted on seismic section, however, small scale fractures show ambiguity in interpretation because fracture in basement rock lies below the seismic wavelength and hence shows erroneous result in identification. Seismic attribute technique also helps us to delineate the seismic fracture and subtle changes in fracture zone and these can be inferred from azimuthal anisotropy in velocity and amplitude and spectral decomposition. Seismic azimuthal anisotropy derives fracture intensity and orientation from compressional wave and converted wave data and based on variation of amplitude or velocity with azimuth. Still detailed analysis of fractured basement required full isotropic and anisotropic analysis of fracture matrix and surrounding rock matrix in order to characterize the spatial variability of basement fracture which support the migration of fluid from basement to overlying rock.

Keywords: basement rock, natural fracture, reservoir characterization, seismic attribute

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Authors: Niharika Kaushal, Minni Singh

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Fruit crops are widely cultivated throughout the World, with citrus being one of the most common. Mandarins, oranges, grapefruits, lemons, and limes are among the most frequently grown varieties. Citrus cultivars are industrially processed into juice, resulting in approx. 25-40% by wt. of biomass in the form of peels and seeds, generally considered as waste. In consequence, a significant amount of this nutraceutical-enriched biomass goes to waste, which, if utilized wisely, could revolutionize the functional food industry, as this biomass possesses a wide range of bioactive compounds, mainly within the class of polyphenols and terpenoids, making them an abundant source of functional bioactive. Mandarin is a potential source of bioflavonoids with putative antioxidative properties, and its potential application for developing value-added products is obvious. In this study, ‘kinnow’ mandarin (Citrus nobilis X Citrus deliciosa) biomass was studied for its flavonoid profile. For this, dried and pulverized peels were subjected to green and sustainable extraction techniques, namely, supercritical fluid extraction carried out under conditions pressure: 330 bar, temperature: 40 ̊ C and co-solvent: 10% ethanol. The obtained extract was observed to contain 47.3±1.06 mg/ml rutin equivalents as total flavonoids. Mass spectral analysis revealed the prevalence of polymethoxyflavones (PMFs), chiefly tangeretin and nobiletin. Furthermore, the antioxidant potential was analyzed by the 2,2-diphenyl-1-picrylhydrazyl (DPPH) method, which was estimated to be at an IC₅₀ of 0.55μg/ml. The pre-systemic metabolism of flavonoids limits their functionality, as was observed in this study through in vitro gastrointestinal studies where nearly 50.0% of the flavonoids were degraded within 2 hours of gastric exposure. We proposed nanoencapsulation as a means to overcome this problem, and flavonoids-laden polylactic-co-glycolic acid (PLGA) nano encapsulates were bioengineered using solvent evaporation method, and these were furnished to a particle size between 200-250nm, which exhibited protection of flavonoids in the gastric environment, allowing only 20% to be released in 2h. A further step involved impregnating the nano encapsulates within alginate hydrogels which were fabricated by ionic cross-linking, which would act as delivery vehicles within the gastrointestinal (GI) tract. As a result, 100% protection was achieved from the pre-systemic release of bioflavonoids. These alginate hydrogels had key significant features, i.e., less porosity of nearly 20.0%, and Cryo-SEM (Cryo-scanning electron microscopy) images of the composite corroborate the packing ability of the alginate hydrogel. As a result of this work, it is concluded that the waste can be used to develop functional biomaterials while retaining the functionality of the bioactive itself.

Keywords: bioflavonoids, gastrointestinal, hydrogels, mandarins

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Authors: Josef Uher, Jana Boháčová, Richard Kadeřábek

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In this paper, we present a multi-robot imaging and irradiation research platform referred to as Irradion, with full capabilities of portable arbitrary path computed tomography (CT). Irradion is an imaging and irradiation unit entirely based on robotic arms for research on cancer treatment with ion beams on small animals (mice or rats). The platform comprises two subsystems that combine several imaging modalities, such as 2D X-ray imaging, CT, and particle tracking, with precise positioning of a small animal for imaging and irradiation. Computed Tomography: The CT subsystem of the Irradion platform is equipped with two 6-joint robotic arms that position a photon counting detector and an X-ray tube independently and freely around the scanned specimen and allow image acquisition utilizing computed tomography. Irradiation measures nearly all conventional 2D and 3D trajectories of X-ray imaging with precisely calibrated and repeatable geometrical accuracy leading to a spatial resolution of up to 50 µm. In addition, the photon counting detectors allow X-ray photon energy discrimination, which can suppress scattered radiation, thus improving image contrast. It can also measure absorption spectra and recognize different materials (tissue) types. X-ray video recording and real-time imaging options can be applied for studies of dynamic processes, including in vivo specimens. Moreover, Irradion opens the door to exploring new 2D and 3D X-ray imaging approaches. We demonstrate in this publication various novel scan trajectories and their benefits. Proton Imaging and Particle Tracking: The Irradion platform allows combining several imaging modules with any required number of robots. The proton tracking module comprises another two robots, each holding particle tracking detectors with position, energy, and time-sensitive sensors Timepix3. Timepix3 detectors can track particles entering and exiting the specimen and allow accurate guiding of photon/ion beams for irradiation. In addition, quantifying the energy losses before and after the specimen brings essential information for precise irradiation planning and verification. Work on the small animal research platform Irradion involved advanced software and hardware development that will offer researchers a novel way to investigate new approaches in (i) radiotherapy, (ii) spectral CT, (iii) arbitrary path CT, (iv) particle tracking. The robotic platform for imaging and radiation research developed for the project is an entirely new product on the market. Preclinical research systems with precision robotic irradiation with photon/ion beams combined with multimodality high-resolution imaging do not exist currently. The researched technology can potentially cause a significant leap forward compared to the current, first-generation primary devices.

Keywords: arbitrary path CT, robotic CT, modular, multi-robot, small animal imaging

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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: Caixia Gao, Chuanrong Li, Lingli Tang, Lingling Ma, Yonggang Qian, Ning Wang

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Knowledge of land surface temperature (LST) is of crucial important in energy balance studies and environment modeling. Satellite thermal infrared (TIR) imagery is the primary source for retrieving LST at the regional and global scales. Due to the combination of atmosphere and land surface of received radiance by TIR sensors, atmospheric effect correction has to be performed to remove the atmospheric transmittance and upwelling radiance. Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard Meteosat Second Generation (MSG) provides measurements every 15 minutes in 12 spectral channels covering from visible to infrared spectrum at fixed view angles with 3km pixel size at nadir, offering new and unique capabilities for LST, LSE measurements. However, due to its high temporal resolution, the atmosphere correction could not be performed with radiosonde profiles or reanalysis data since these profiles are not available at all SEVIRI TIR image acquisition times. To solve this problem, a two-part six-parameter semi-empirical diurnal temperature cycle (DTC) model has been applied to the temporal interpolation of ECMWF reanalysis data. Due to the fact that the DTC model is underdetermined with ECMWF data at four synoptic times (UTC times: 00:00, 06:00, 12:00, 18:00) in one day for each location, some approaches are adopted in this study. It is well known that the atmospheric transmittance and upwelling radiance has a relationship with water vapour content (WVC). With the aid of simulated data, the relationship could be determined under each viewing zenith angle for each SEVIRI TIR channel. Thus, the atmospheric transmittance and upwelling radiance are preliminary removed with the aid of instantaneous WVC, which is retrieved from the brightness temperature in the SEVIRI channels 5, 9 and 10, and a group of the brightness temperatures for surface leaving radiance (Tg) are acquired. Subsequently, a group of the six parameters of the DTC model is fitted with these Tg by a Levenberg-Marquardt least squares algorithm (denoted as DTC model 1). Although the retrieval error of WVC and the approximate relationships between WVC and atmospheric parameters would induce some uncertainties, this would not significantly affect the determination of the three parameters, td, ts and β (β is the angular frequency, td is the time where the Tg reaches its maximum, ts is the starting time of attenuation) in DTC model. Furthermore, due to the large fluctuation in temperature and the inaccuracy of the DTC model around sunrise, SEVIRI measurements from two hours before sunrise to two hours after sunrise are excluded. With the knowledge of td , ts, and β, a new DTC model (denoted as DTC model 2) is accurately fitted again with these Tg at UTC times: 05:57, 11:57, 17:57 and 23:57, which is atmospherically corrected with ECMWF data. And then a new group of the six parameters of the DTC model is generated and subsequently, the Tg at any given times are acquired. Finally, this method is applied to SEVIRI data in channel 9 successfully. The result shows that the proposed method could be performed reasonably without assumption and the Tg derived with the improved method is much more consistent with that from radiosonde measurements.

Keywords: atmosphere correction, diurnal temperature cycle model, land surface temperature, SEVIRI

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Authors: Antonina Semakova, Karim Mynbaev, Nikolai Bazhenov, Anton Chernyaev, Sergei Kizhaev, Nikolai Stoyanov

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At present, heterostructures are used for fabrication of almost all types of optoelectronic devices. Our research focuses on the optoelectronic properties of InAs(Sb) solid solutions that are widely used in fabrication of light emitting diodes (LEDs) operating in middle wavelength infrared range (MWIR). This spectral range (2-6 μm) is relevant for laser diode spectroscopy of gases and molecules, for systems for the detection of explosive substances, medical applications, and for environmental monitoring. The fabrication of MWIR LEDs that operate efficiently at room temperature is mainly hindered by the predominance of non-radiative Auger recombination of charge carriers over the process of radiative recombination, which makes practical application of LEDs difficult. However, non-radiative recombination can be partly suppressed in quantum-well structures. In this regard, studies of such structures are quite topical. In this work, electroluminescence (EL) of LED heterostructures based on InAs(Sb) epitaxial films with the molar fraction of InSb ranging from 0 to 0.09 and multi quantum-well (MQW) structures was studied in the temperature range 4.2-300 K. The growth of the heterostructures was performed by metal-organic chemical vapour deposition on InAs substrates. On top of the active layer, a wide-bandgap InAsSb(Ga,P) barrier was formed. At low temperatures (4.2-100 K) stimulated emission was observed. As the temperature increased, the emission became spontaneous. The transition from stimulated emission to spontaneous one occurred at different temperatures for structures with different InSb contents in the active region. The temperature-dependent carrier lifetime, limited by radiative recombination and the most probable Auger processes (for the materials under consideration, CHHS and CHCC), were calculated within the framework of the Kane model. The effect of various recombination processes on the carrier lifetime was studied, and the dominant role of Auger processes was established. For MQW structures quantization energies for electrons, light and heavy holes were calculated. A characteristic feature of the experimental EL spectra of these structures was the presence of peaks with energy different from that of calculated optical transitions between the first quantization levels for electrons and heavy holes. The obtained results showed strong effect of the specific electronic structure of InAsSb on the energy and intensity of optical transitions in nanostructures based on this material. For the structure with MQWs in the active layer, a very weak temperature dependence of EL peak was observed at high temperatures (>150 K), which makes it attractive for fabricating temperature-resistant gas sensors operating in the middle-infrared range.

Keywords: Electroluminescence, InAsSb, light emitting diode, quantum wells

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Authors: Yildiz Stella Dak, Jale Tezcan

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Ground motion models that relate a strong motion parameter of interest to a set of predictive seismological variables describing the earthquake source, the propagation path of the seismic wave, and the local site conditions constitute a critical component of seismic hazard analyses. When a sufficient number of strong motion records are available, ground motion relations are developed using statistical analysis of the recorded ground motion data. In regions lacking a sufficient number of recordings, a synthetic database is developed using stochastic, theoretical or hybrid approaches. Regardless of the manner the database was developed, ground motion relations are developed using regression analysis. Development of a ground motion relation is a challenging process which inevitably requires the modeler to make subjective decisions regarding the inclusion criteria of the recordings, the functional form of the model and the set of seismological variables to be included in the model. Because these decisions are critically important to the validity and the applicability of the model, there is a continuous interest on procedures that will facilitate the development of ground motion models. This paper proposes the use of the Least Absolute Shrinkage and Selection Operator (LASSO) in selecting the set predictive seismological variables to be used in developing a ground motion relation. The LASSO can be described as a penalized regression technique with a built-in capability of variable selection. Similar to the ridge regression, the LASSO is based on the idea of shrinking the regression coefficients to reduce the variance of the model. Unlike ridge regression, where the coefficients are shrunk but never set equal to zero, the LASSO sets some of the coefficients exactly to zero, effectively performing variable selection. Given a set of candidate input variables and the output variable of interest, LASSO allows ranking the input variables in terms of their relative importance, thereby facilitating the selection of the set of variables to be included in the model. Because the risk of overfitting increases as the ratio of the number of predictors to the number of recordings increases, selection of a compact set of variables is important in cases where a small number of recordings are available. In addition, identification of a small set of variables can improve the interpretability of the resulting model, especially when there is a large number of candidate predictors. A practical application of the proposed approach is presented, using more than 600 recordings from the National Geospatial-Intelligence Agency (NGA) database, where the effect of a set of seismological predictors on the 5% damped maximum direction spectral acceleration is investigated. The set of candidate predictors considered are Magnitude, Rrup, Vs30. Using LASSO, the relative importance of the candidate predictors has been ranked. Regression models with increasing levels of complexity were constructed using one, two, three, and four best predictors, and the models’ ability to explain the observed variance in the target variable have been compared. The bias-variance trade-off in the context of model selection is discussed.

Keywords: ground motion modeling, least absolute shrinkage and selection operator, penalized regression, variable selection

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Authors: Ekaterina A. Savchenko, Elena N. Velichko, Evgenii T. Aksenov

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The development of pathological processes, such as cardiovascular and oncological diseases, are accompanied by changes in molecular parameters in cells, tissues, and serum. The study of the behavior of protein molecules in solutions is of primarily importance for diagnosis of such diseases. Various physical and chemical methods are used to study molecular systems. With the advent of the laser and advances in electronics, optical methods, such as scanning electron microscopy, sedimentation analysis, nephelometry, static and dynamic light scattering, have become the most universal, informative and accurate tools for estimating the parameters of nanoscale objects. The electrophoretic light scattering is the most effective technique. It has a high potential in the study of biological solutions and their properties. This technique allows one to investigate the processes of aggregation and dissociation of different macromolecules and obtain information on their shapes, sizes and molecular weights. Electrophoretic light scattering is an analytical method for registration of the motion of microscopic particles under the influence of an electric field by means of quasi-elastic light scattering in a homogeneous solution with a subsequent registration of the spectral or correlation characteristics of the light scattered from a moving object. We modified the technique by using the regime of total internal reflection with the aim of increasing its sensitivity and reducing the volume of the sample to be investigated, which opens the prospects of automating simultaneous multiparameter measurements. In addition, the method of total internal reflection allows one to study biological fluids on the level of single molecules, which also makes it possible to increase the sensitivity and the informativeness of the results because the data obtained from an individual molecule is not averaged over an ensemble, which is important in the study of bimolecular fluids. To our best knowledge the study of electrophoretic light scattering in the regime of total internal reflection is proposed for the first time, latex microspheres 1 μm in size were used as test objects. In this study, the total internal reflection regime was realized on a quartz prism where the free electrophoresis regime was set. A semiconductor laser with a wavelength of 655 nm was used as a radiation source, and the light scattering signal was registered by a pin-diode. Then the signal from a photodetector was transmitted to a digital oscilloscope and to a computer. The autocorrelation functions and the fast Fourier transform in the regime of Brownian motion and under the action of the field were calculated to obtain the parameters of the object investigated. The main result of the study was the dependence of the autocorrelation function on the concentration of microspheres and the applied field magnitude. The effect of heating became more pronounced with increasing sample concentrations and electric field. The results obtained in our study demonstrated the applicability of the method for the examination of liquid solutions, including biological fluids.

Keywords: light scattering, electrophoretic light scattering, electrophoresis, total internal reflection

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Authors: Teng Li, Kamran Mohseni

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This paper presents an inviscid regularization technique for the incompressible two-phase flow simulations. This technique is known as observable method due to the understanding of observability that any feature smaller than the actual resolution (physical or numerical), i.e., the size of wire in hotwire anemometry or the grid size in numerical simulations, is not able to be captured or observed. Differ from most regularization techniques that applies on the numerical discretization, the observable method is employed at PDE level during the derivation of equations. Difficulties in the simulation and analysis of realistic fluid flow often result from discontinuities (or near-discontinuities) in the calculated fluid properties or state. Accurately capturing these discontinuities is especially crucial when simulating flows involving shocks, turbulence or sharp interfaces. Over the past several years, the properties of this new regularization technique have been investigated that show the capability of simultaneously regularizing shocks and turbulence. The observable method has been performed on the direct numerical simulations of shocks and turbulence where the discontinuities are successfully regularized and flow features are well captured. In the current paper, the observable method will be extended to two-phase interfacial flows. Multiphase flows share the similar features with shocks and turbulence that is the nonlinear irregularity caused by the nonlinear terms in the governing equations, namely, Euler equations. In the direct numerical simulation of two-phase flows, the interfaces are usually treated as the smooth transition of the properties from one fluid phase to the other. However, in high Reynolds number or low viscosity flows, the nonlinear terms will generate smaller scales which will sharpen the interface, causing discontinuities. Many numerical methods for two-phase flows fail at high Reynolds number case while some others depend on the numerical diffusion from spatial discretization. The observable method regularizes this nonlinear mechanism by filtering the convective terms and this process is inviscid. The filtering effect is controlled by an observable scale which is usually about a grid length. Single rising bubble and Rayleigh-Taylor instability are studied, in particular, to examine the performance of the observable method. A pseudo-spectral method is used for spatial discretization which will not introduce numerical diffusion, and a Total Variation Diminishing (TVD) Runge Kutta method is applied for time integration. The observable incompressible Euler equations are solved for these two problems. In rising bubble problem, the terminal velocity and shape of the bubble are particularly examined and compared with experiments and other numerical results. In the Rayleigh-Taylor instability, the shape of the interface are studied for different observable scale and the spike and bubble velocities, as well as positions (under a proper observable scale), are compared with other simulation results. The results indicate that this regularization technique can potentially regularize the sharp interface in the two-phase flow simulations

Keywords: Euler equations, incompressible flow simulation, inviscid regularization technique, two-phase flow

Procedia PDF Downloads 502

Authors: Maia Kharadze, Indira Djaparidze, Maia Vanidze, Aleko Kalandia

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Modern scientific world studies chemical components and antioxidant activity of different kinds of vines according to their breed purity and location. To our knowledge, this kind of research has not been conducted in Georgia yet. The object of our research was to study Chkhaveri vine, which is included in the oldest varieties of the Black Sea basin vine. We have studied different-altitude Chkaveri grapes, juice, and wine (half dry rose-colored produced with European technologies) and their technical markers, qualitative and quantitive composition of their biologically active compounds and their antioxidant activity. We were determining the amount of phenols using Folin-Ciocalteu reagent, Flavonoids, Catechins and Anthocyanins using Spectral method and antioxidant activity using DPPH method. Several compounds were identified using –HPLC-UV-Vis, UPLC-MS methods. Six samples of Chkhaveri species– 5, 300, 360, 380, 400, 780 meter altitudes were taken and analyzed. The sample taken from 360 m altitude is distinguished by its cluster mass (383.6 grams) and high amount of sugar (20.1%). The sample taken from the five-meter altitude is distinguished by having high acidity (0.95%). Unlike other grapes varieties, such concentration of sugar and relatively low levels of citric acid ultimately leads to Chkhaveri wine individuality. Biologically active compounds of Chkhaveri were researched in 2014, 2015, 2016. The amount of total phenols in samples of 2016 fruit varies from 976.7 to 1767.0 mg/kg. Amount of Anthocians is 721.2-1630.2 mg/kg, and the amount of Flavanoids varies from 300.6 to 825.5 mg/kg. Relatively high amount of anthocyanins was found in the Chkhaveri at 780-meter altitude - 1630.2 mg/kg. Accordingly, the amount of Phenols and Flavanoids is high- 1767.9 mg/kg and 825.5 mg/kg. These characteristics are low in samples gathered from 5 meters above sea level, Anthocyanins-721.2 mg/ kg, total Phenols-976.7 mg/ kg, and Flavanoids-300.6 mg/kg. The highest amount of bioactive compounds can be found in the Chkhaveri samples of high altitudes because with rising height environment becomes harsh, the plant has to develop a better immune system using Phenolic compounds. The technology that is used for the production of wine also plays a huge role in the composition of the final product. Optimal techniques of maceration and ageing were worked out. While squeezing Chkhaveri, there are no anthocyanins in the juice. However, the amount of Anthocyanins rises during maceration. After the fermentation of dregs, the amount of anthocyanins is 55%, 521.3 gm/l, total Phenols 80% 1057.7 mg/l and Flavanoids 23.5 mg/l. Antioxidant activity of samples was also determined using the effect of 50% inhibition of the samples. All samples have high antioxidant activity. For instance, in samples at 780 meters above the sea-level antioxidant activity was 53.5%. It is relatively high compared to the sample at 5 m above sea-level with the antioxidant activity of 30.5%. Thus, there is a correlation between the amount Anthocyanins and antioxidant activity. The designated project has been fulfilled by financial support of the Georgia National Science Foundation (Grant AP/96/13, Grant 216816), Any idea in this publication is possessed by the author and may not represent the opinion of the Georgia National Science Foundation.

Keywords: antioxidants, bioactive content, wine, chkhaveri

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Authors: Elham Koohikerade, Silvio Jose Gumiere

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In this research, irrigation is highlighted as crucial for improving both the yield and quality of ‎potatoes due to their high sensitivity to soil moisture changes. The study presents a hybrid Long ‎Short-Term Memory (LSTM) model aimed at optimizing irrigation scheduling in potato fields in ‎Quebec City, Canada. This model integrates model-based and satellite-derived datasets to simulate ‎soil moisture content, addressing the limitations of field data. Developed under the guidance of the ‎Food and Agriculture Organization (FAO), the simulation approach compensates for the lack of direct ‎soil sensor data, enhancing the LSTM model's predictions. The model was calibrated using indices ‎like Surface Soil Moisture (SSM), Normalized Vegetation Difference Index (NDVI), Enhanced ‎Vegetation Index (EVI), and Normalized Multi-band Drought Index (NMDI) to effectively forecast ‎soil moisture reductions. Understanding soil moisture and plant development is crucial for assessing ‎drought conditions and determining irrigation needs. This study validated the spectral characteristics ‎of vegetation and soil using ECMWF Reanalysis v5 (ERA5) and Moderate Resolution Imaging ‎Spectrometer (MODIS) data from 2019 to 2023, collected from agricultural areas in Dolbeau and ‎Peribonka, Quebec. Parameters such as surface volumetric soil moisture (0-7 cm), NDVI, EVI, and ‎NMDI were extracted from these images. A regional four-year dataset of soil and vegetation moisture ‎was developed using a machine learning approach combining model-based and satellite-based ‎datasets. The LSTM model predicts soil moisture dynamics hourly across different locations and ‎times, with its accuracy verified through cross-validation and comparison with existing soil moisture ‎datasets. The model effectively captures temporal dynamics, making it valuable for applications ‎requiring soil moisture monitoring over time, such as anomaly detection and memory analysis. By ‎identifying typical peak soil moisture values and observing distribution shapes, irrigation can be ‎scheduled to maintain soil moisture within Volumetric Soil Moisture (VSM) values of 0.25 to 0.30 ‎m²/m², avoiding under and over-watering. The strong correlations between parcels suggest that a ‎uniform irrigation strategy might be effective across multiple parcels, with adjustments based on ‎specific parcel characteristics and historical data trends. The application of the LSTM model to ‎predict soil moisture and vegetation indices yielded mixed results. While the model effectively ‎captures the central tendency and temporal dynamics of soil moisture, it struggles with accurately ‎predicting EVI, NDVI, and NMDI.‎

Keywords: irrigation scheduling, LSTM neural network, remotely sensed indices, soil and vegetation ‎monitoring

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Authors: Ieva Jokubauskaite, Alvyra Slepetiene, Danute Karcauskiene, Inga Liaudanskiene, Kristina Amaleviciute

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Soil organic carbon (SOC) is the key soil quality and ecological stability indicator, therefore, carbon accumulation in stable forms not only supports and increases the organic matter content in the soil, but also has a positive effect on the quality of soil and the whole ecosystem. Soil liming is one of the most common ways to improve the carbon sequestration in the soil. Determination of the optimum intensity and combinations of liming in order to ensure the optimal carbon quantitative and qualitative parameters is one of the most important tasks of this work. The field experiments were carried out at the Vezaiciai Branch of Lithuanian Research Centre for Agriculture and Forestry (LRCAF) during the 2011–2013 period. The effect of liming with different intensity (at a rate 0.5 every 7 years and 2.0 every 3-4 years) was investigated in the topsoil of acid moraine loam Bathygleyic Dystric Glossic Retisol. Chemical analyses were carried out at the Chemical Research Laboratory of Institute of Agriculture, LRCAF. Soil samples for chemical analyses were taken from the topsoil after harvesting. SOC was determined by the Tyurin method modified by Nikitin, measuring with spectrometer Cary 50 (VARIAN) at 590 nm wavelength using glucose standards. SOC fractional composition was determined by Ponomareva and Plotnikova version of classical Tyurin method. Dissolved organic carbon (DOC) was analyzed using an ion chromatograph SKALAR in water extract at soil-water ratio 1:5. Spectral properties (E4/E6 ratio) of humic acids were determined by measuring the absorbance of humic and fulvic acids solutions at 465 and 665 nm. Our study showed a negative statistically significant effect of periodical liming (at 0.5 and 2.0 liming rates) on SOC content in the soil. The content of SOC was 1.45% in the unlimed treatment, while in periodically limed at 2.0 liming rate every 3–4 years it was approximately by 0.18 percentage points lower. It was revealed that liming significantly decreased the DOC concentration in the soil. The lowest concentration of DOC (0.156 g kg-1) was established in the most intensively limed (2.0 liming rate every 3–4 years) treatment. Soil liming exerted an increase of all humic acids and fulvic acid bounded with calcium fractions content in the topsoil. Soil liming resulted in the accumulation of valuable humic acids. Due to the applied liming, the HR/FR ratio, indicating the quality of humus increased to 1.08 compared with that in unlimed soil (0.81). Intensive soil liming promoted the formation of humic acids in which groups of carboxylic and phenolic compounds predominated. These humic acids are characterized by a higher degree of condensation of aromatic compounds and in this way determine the intensive organic matter humification processes in the soil. The results of this research provide us with the clear information on the characteristics of SOC change, which could be very useful to guide the climate policy and sustainable soil management.

Keywords: acid soil, carbon sequestration, long–term liming, soil organic carbon

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Authors: Uraib Sharaha, Ahmad Salman, Eladio Rodriguez-Diaz, Elad Shufan, Klaris Riesenberg, Irving J. Bigio, Mahmoud Huleihel

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Antimicrobial drugs have played an indispensable role in controlling illness and death associated with infectious diseases in animals and humans. However, the increasing resistance of bacteria to a broad spectrum of commonly used antibiotics has become a global healthcare problem. Many antibiotics had lost their effectiveness since the beginning of the antibiotic era because many bacteria have adapted defenses against these antibiotics. Rapid determination of antimicrobial susceptibility of a clinical isolate is often crucial for the optimal antimicrobial therapy of infected patients and in many cases can save lives. The conventional methods for susceptibility testing require the isolation of the pathogen from a clinical specimen by culturing on the appropriate media (this culturing stage lasts 24 h-first culturing). Then, chosen colonies are grown on media containing antibiotic(s), using micro-diffusion discs (second culturing time is also 24 h) in order to determine its bacterial susceptibility. Other methods, genotyping methods, E-test and automated methods were also developed for testing antimicrobial susceptibility. Most of these methods are expensive and time-consuming. Fourier transform infrared (FTIR) microscopy is rapid, safe, effective and low cost method that was widely and successfully used in different studies for the identification of various biological samples including bacteria; nonetheless, its true potential in routine clinical diagnosis has not yet been established. The new modern infrared (IR) spectrometers with high spectral resolution enable measuring unprecedented biochemical information from cells at the molecular level. Moreover, the development of new bioinformatics analyses combined with IR spectroscopy becomes a powerful technique, which enables the detection of structural changes associated with resistivity. The main goal of this study is to evaluate the potential of the FTIR microscopy in tandem with machine learning algorithms for rapid and reliable identification of bacterial susceptibility to antibiotics in time span of few minutes. The UTI E.coli bacterial samples, which were identified at the species level by MALDI-TOF and examined for their susceptibility by the routine assay (micro-diffusion discs), are obtained from the bacteriology laboratories in Soroka University Medical Center (SUMC). These samples were examined by FTIR microscopy and analyzed by advanced statistical methods. Our results, based on 700 E.coli samples, were promising and showed that by using infrared spectroscopic technique together with multivariate analysis, it is possible to classify the tested bacteria into sensitive and resistant with success rate higher than 90% for eight different antibiotics. Based on these preliminary results, it is worthwhile to continue developing the FTIR microscopy technique as a rapid and reliable method for identification antibiotic susceptibility.

Keywords: antibiotics, E.coli, FTIR, multivariate analysis, susceptibility, UTI

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Authors: Mustapha A. Tijjani, Fanna I. Abdulrahman, Irfan Z. Khan, Umar K. Sandabe, Cong Li

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Air dried sample V. doniana after collection and identification was extracted with ethanol and further partition with chloroform, ethyl acetate and n-butanol. Ethanolic extract (11.9g) was fractionated on a silica gel accelerated column chromatography using solvents such as n-hexane, ethyl acetate and methanol. Each eluent fractions (150ml aliquots) were collected and monitored with thin layer chromatography. Fractions with similar Rf values from same solvents system were pooled together. Phytochemical test of all the fractions were performed using standard procedure. Complete elution yielded 48 fractions (150ml/fraction) which were pooled to 24 fractions base on the Rf values. It was further recombined and 12 fractions were obtained on the basis on Rf values and coded Vd1 to Vd12 fractions. Vd8 was further eluted with ethylacetate and methanol and gave fourteen sub fractions Vd8-a, -Vd8-m. Fraction Vd8-a (56mg) gave a white crystal compound coded V1. It was further checked on TLC and observed under ultraviolet lamp and was found to give a single spot. The Rf values were calculated to be 0.433. The melting point was determined using Gallenkamp capillary melting point apparatus and found to be 241-243°C uncorrected. Characterization of the isolated compound coded V1 was done using FT-infra-red spectroscopy, HNMR, 13CNMR(1and 2D) and HRESI-MS. The IR spectrum of compound V1 shows prominent peaks that corresponds to OHstr (3365cm-1) and C=0 (1652cm-1) etc. This spectrum suggests that among the functional moiety in compound V1 are the carbonyl and hydroxyl group. The 1H NMR (400 MHz) spectrum of compound V1 in DMSO-d6 displayed five singlet signals at δ 0.72 (3H, s, H-18), 0.79 (3H, s, H-19), 1.03 (3H, s, H-21), 1.04 (3H, s, H-26), 1.06 (3H, s, H-27) each integrating for three protons indicating the five methyl functional groups present in the compound. It further showed a broad singlet at δ 5.58 integrated for 1 H due to an olefinic H-atom adjacent to the carbonyl carbon atom. Three signals at δ 3.10 (d, J = 9.0 Hz, H-22), 3.59 (m, 1H, 2H-a) and 3.72 (m, 1H, 3H-e), each integrating for one proton is due to oxymethine protons indicating that three oxymethine H-atoms are present in the compound. These all signals are characteristic to the ecdysteroid skeletons. The 13C-NMR spectrum showed the presence of 27 carbon atoms, suggesting that may be steroid skeleton. The DEPT-135 experiment showed the presence of five CH3, eight CH2, and seven CH groups, and seven quaternary C-atoms. The molecular formula was established as C27H44O7 by high resolution electron spray ionization-mass spectroscopy (HRESI-MS) positive ion mode m/z 481.3179. The signals in mass spectrum are 463, 445, and 427 peaks corresponding to losses of one, two, three, or four water molecules characteristic for ecdysterone skeleton reported in the literature. Based on the spectral analysis (HNMR, 13CNMR, DEPT, HMQC, IR, HRESI-MS) the compound V1 is thus concluded to have ecdysteriod skeleton and conclusively conforms with 2β, 3β 14α, 20R, 22R, 25-hexahydroxy-5 β cholest-7-ene-6- one, or 2, 3, 14, 20, 22, 25 hexahydroxy cholest-7-ene-6-one commonly known as 20-hydroxyecdysone.

Keywords: vitex, phytochemical, purification, isolation, chromatography, spectroscopy

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Authors: Ruijia Hu, Susanna T.Y. Tong

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Light detection and ranging (LiDAR) and four-channel red, green, blue, and near-infrared (RGBI) remote sensed imageries allow an accurate quantification and contiguous measurement of vegetation characteristics and forest structures. This information facilitates the generation of habitat structure variables for forest species distribution modelling. However, applications of remote sensing data, especially the combination of structural and spectral information, to support evidence-based decisions in forest managements and conservation practices at local scale are not widely adopted. In this study, we examined the habitat requirements of pileated woodpecker (Dryocopus pileatus) (PW) in Hamilton County, Ohio, using ecologically relevant forest structural and vegetation characteristics derived from LiDAR and RGBI data. We hypothesized that the habitat of PW is shaped by vegetation characteristics that are directly associated with the availability of food, hiding and nesting resources, the spatial arrangement of habitat patches within home range, as well as proximity to water sources. We used 186 PW presence or absence locations to model their presence and absence in generalized additive model (GAM) at two scales, representing foraging and home range size, respectively. The results confirm PW’s preference for tall and large mature stands with structural complexity, typical of late-successional or old-growth forests. Besides, the crown size of dead trees shows a positive relationship with PW occurrence, therefore indicating the importance of declining living trees or early-stage dead trees within PW home range. These locations are preferred by PW for nest cavity excavation as it attempts to balance the ease of excavation and tree security. In addition, we found that PW can adjust its travel distance to the nearest water resource, suggesting that habitat fragmentation can have certain impacts on PW. Based on our findings, we recommend that forest managers should use different priorities to manage nesting, roosting, and feeding habitats. Particularly, when devising forest management and hazard tree removal plans, one needs to consider retaining enough cavity trees within high-quality PW habitat. By mapping PW habitat suitability for the study area, we highlight the importance of riparian corridor in facilitating PW to adjust to the fragmented urban landscape. Indeed, habitat improvement for PW in the study area could be achieved by conserving riparian corridors and promoting riparian forest succession along major rivers in Hamilton County.

Keywords: deadwood detection, generalized additive model, individual tree crown delineation, LiDAR, pileated woodpecker, RGBI aerial imagery, species distribution models

Procedia PDF Downloads 53

Authors: Radik D. Aglyamov, Alexander K. Naumov, Alexey A. Shavelev, Oleg A. Morozov, Arsenij D. Shishkin, Yury P.Brodnikovsky, Alexander A.Karabutov, Alexander A. Oraevsky, Vadim V. Semashko

Abstract:

The development of medical optoacoustic tomography with the using human blood as endogenic contrast agent is constrained by the lack of reliable, easy-to-use and inexpensive sources of high-power pulsed laser radiation in the spectral region of 750-900 nm [1-2]. Currently used titanium-sapphire, alexandrite lasers or optical parametric light oscillators do not provide the required and stable output characteristics, they are structurally complex, and their cost is up to half the price of diagnostic optoacoustic systems. Here we are developing the lasers based on Cr:LiCaAlF6 crystals which are free of abovementioned disadvantages and provides intensive ten’s ns-range tunable laser radiation at specific absorption bands of oxy- (~840 nm) and -deoxyhemoglobin (~757 nm) in the blood. Cr:LiCAF (с=3 at.%) crystals were grown in Kazan Federal University by the vertical directional crystallization (Bridgman technique) in graphite crucibles in a fluorinating atmosphere at argon overpressure (P=1500 hPa) [3]. The laser elements have cylinder shape with the diameter of 8 mm and 90 mm in length. The direction of the optical axis of the crystal was normal to the cylinder generatrix, which provides the π-polarized laser action correspondent to maximal stimulated emission cross-section. The flat working surfaces of the active elements were polished and parallel to each other with an error less than 10”. No any antireflection coating was applied. The Q-switched master oscillator-power amplifiers laser system (MOPA) with the dual-Xenon flashlamp pumping scheme in diffuse-reflectivity close-coupled head were realized. A specially designed laser cavity, consisting of dielectric highly reflective reflectors with a 2 m-curvature radius, a flat output mirror, a polarizer and Q-switch sell, makes it possible to operate sequentially in a circle (50 ns - laser one pulse after another) at wavelengths of 757 and 840 nm. The programmable pumping system from Tomowave Laser LLC (Russia) provided independent to each pulses (up to 250 J at 180 μs) pumping to equalize the laser radiation intensity at these wavelengths. The MOPA laser operates at 10 Hz pulse repetition rate with the output energy up to 210 mJ. Taking into account the limitations associated with physiological movements and other characteristics of patient tissues, the duration of laser pulses and their energy allows molecular and functional high-contrast imaging to depths of 5-6 cm with a spatial resolution of at least 1 mm. Highly likely the further comprehensive design of laser allows improving the output properties and realizing better spatial resolution of medical multispectral optoacoustic tomography systems.

Keywords: medical optoacoustic, endogenic contrast agent, multiwavelength tunable pulse lasers, MOPA laser system

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Authors: Mercedes Bertotto, Marcelo Bello, Hector Goicoechea, Veronica Fusca

Abstract:

The National Service of Agri-Food Health and Quality (SENASA), controls honey to detect contamination by synthetic or natural chemical substances and establishes and controls the traceability of the product. The utility of near-infrared spectroscopy for the detection of adulteration of honey with high fructose corn syrup (HFCS) was investigated. First of all, a mixture of different authentic artisanal Argentinian honey was prepared to cover as much heterogeneity as possible. Then, mixtures were prepared by adding different concentrations of high fructose corn syrup (HFCS) to samples of the honey pool. 237 samples were used, 108 of them were authentic honey and 129 samples corresponded to honey adulterated with HFCS between 1 and 10%. They were stored unrefrigerated from time of production until scanning and were not filtered after receipt in the laboratory. Immediately prior to spectral collection, honey was incubated at 40°C overnight to dissolve any crystalline material, manually stirred to achieve homogeneity and adjusted to a standard solids content (70° Brix) with distilled water. Adulterant solutions were also adjusted to 70° Brix. Samples were measured by NIR spectroscopy in the range of 650 to 7000 cm⁻¹. The technique of specular reflectance was used, with a lens aperture range of 150 mm. Pretreatment of the spectra was performed by Standard Normal Variate (SNV). The ant colony optimization genetic algorithm sample selection (ACOGASS) graphical interface was used, using MATLAB version 5.3, to select the variables with the greatest discriminating power. The data set was divided into a validation set and a calibration set, using the Kennard-Stone (KS) algorithm. A combined method of Potential Functions (PF) was chosen together with Partial Least Square Linear Discriminant Analysis (PLS-DA). Different estimators of the predictive capacity of the model were compared, which were obtained using a decreasing number of groups, which implies more demanding validation conditions. The optimal number of latent variables was selected as the number associated with the minimum error and the smallest number of unassigned samples. Once the optimal number of latent variables was defined, we proceeded to apply the model to the training samples. With the calibrated model for the training samples, we proceeded to study the validation samples. The calibrated model that combines the potential function methods and PLSDA can be considered reliable and stable since its performance in future samples is expected to be comparable to that achieved for the training samples. By use of Potential Functions (PF) and Partial Least Square Linear Discriminant Analysis (PLS-DA) classification, authentic honey and honey adulterated with HFCS could be identified with a correct classification rate of 97.9%. The results showed that NIR in combination with the PT and PLS-DS methods can be a simple, fast and low-cost technique for the detection of HFCS in honey with high sensitivity and power of discrimination.

Keywords: adulteration, multivariate analysis, potential functions, regression

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Authors: Farhan A. Alenizi

Abstract:

Digital watermarking has evolved in the past years as an important means for data authentication and ownership protection. The images and video watermarking was well known in the field of multimedia processing; however, 3D objects' watermarking techniques have emerged as an important means for the same purposes, as 3D mesh models are in increasing use in different areas of scientific, industrial, and medical applications. Like the image watermarking techniques, 3D watermarking can take place in either space or transform domains. Unlike images and video watermarking, where the frames have regular structures in both space and temporal domains, 3D objects are represented in different ways as meshes that are basically irregular samplings of surfaces; moreover, meshes can undergo a large variety of alterations which may be hard to tackle. This makes the watermarking process more challenging. While the transform domain watermarking is preferable in images and videos, they are still difficult to implement in 3d meshes due to the huge number of vertices involved and the complicated topology and geometry, and hence the difficulty to perform the spectral decomposition, even though significant work was done in the field. Spatial domain watermarking has attracted significant attention in the past years; they can either act on the topology or on the geometry of the model. Exploiting the statistical characteristics in the 3D mesh models from both geometrical and topological aspects was useful in hiding data. However, doing that with minimal surface distortions to the mesh attracted significant research in the field. A 3D mesh blind watermarking technique is proposed in this research. The watermarking method depends on modifying the vertices' positions with respect to the center of the object. An optimal method will be developed to reduce the errors, minimizing the distortions that the 3d object may experience due to the watermarking process, and reducing the computational complexity due to the iterations and other factors. The technique relies on the displacement process of the vertices' locations depending on the modification of the variances of the vertices’ norms. Statistical analyses were performed to establish the proper distributions that best fit each mesh, and hence establishing the bins sizes. Several optimizing approaches were introduced in the realms of mesh local roughness, the statistical distributions of the norms, and the displacements in the mesh centers. To evaluate the algorithm's robustness against other common geometry and connectivity attacks, the watermarked objects were subjected to uniform noise, Laplacian smoothing, vertices quantization, simplification, and cropping. Experimental results showed that the approach is robust in terms of both perceptual and quantitative qualities. It was also robust against both geometry and connectivity attacks. Moreover, the probability of true positive detection versus the probability of false-positive detection was evaluated. To validate the accuracy of the test cases, the receiver operating characteristics (ROC) curves were drawn, and they’ve shown robustness from this aspect. 3D watermarking is still a new field but still a promising one.

Keywords: watermarking, mesh objects, local roughness, Laplacian Smoothing

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Authors: K. J. Sannapapamma, H. Malligawad Lokanath, Sakeena Naikwadi

Abstract:

Eco-friendly textiles are gaining importance among the consumers and textile manufacturers in the healthcare sector due to increased environmental pollution which leads to several health and environmental hazards. Hence, the research was designed to cultivate and develop the organic cotton knit, to prepare and characterize the Vetiver oil microcapsules for textile finishing and to access the wash durability of finished knits. The cotton SAHANA variety grown under organic production systems was processed and spun into 30 single yarn dyed with four natural colorants (Arecanut slurry, Eucalyptus leaves, Pomegranate rind and Indigo) and eco dyed yarn was further used for development of single jersy knitted fabric. Vetiveria zizanioides is an aromatic grass which is being traditionally used in medicine and perfumery. Vetiver essential oil was used for preparation of microcapsules by interfacial polymerization technique subjected to Gas Chromatography Mass Spectrometry (GCMS), Fourier Transform Infrared Spectroscopy (FTIR), Thermo Gravimetric Analyzer (TGA) and Scanning Electron Microscope (SEM) for characterization of microcapsules. The knitted fabric was finished with vetiver oil microcapsules by exhaust and pad dry cure methods. The finished organic knit was assessed for laundering on antimicrobial efficiency and aroma intensity. GCMS spectral analysis showed that, diethyl phthalate (28%) was the major compound found in vetiver oil followed by isoaromadendrene epoxide (7.72%), beta-vetivenene (6.92%), solavetivone (5.58%), aromadenderene, azulene and khusimol. Bioassay explained that, the vetiver oil and diluted vetiver oil possessed greater zone of inhibition against S. aureus and E. coli than the coconut oil. FTRI spectra of vetiver oil and microcapsules possessed similar peaks viz., C-H, C=C & C꞊O stretching and additionally oil microcapsules possessed the peak of 3331.24 cm^-1 at 91.14 transmittance was attributed to N-H stretches. TGA of oil microcapsules revealed that, there was a minimum weight loss (5.835%) recorded at 467.09°C compared to vetiver oil i.e., -3.026% at the temperature of 396.24°C. The shape of the microcapsules was regular and round, some were spherical in shape and few were rounded by small aggregates. Irrespective of methods of application, organic cotton knits finished with microcapsules by pad dry cure method showed maximum zone of inhibition compared to knits finished by exhaust method against S. aureus and E. coli. The antimicrobial activity of the finished samples was subjected to multiple washing which indicated that knits finished with pad dry cure method showed a zone of inhibition even after 20^th wash and better aroma retention compared to knits finished with the exhaust method of application. Further, the group of respondents rated that the 5^th washed samples had the greater aroma intensity in both the methods than the other samples. Thus, the vetiver microencapsulated organic cotton knits are free from hazardous chemicals and have multi-functional properties that can be suitable for medical and healthcare textiles.

Keywords: exhaust and pad dry cure finishing, interfacial polymerization, organic cotton knits, vetiver oil microcapsules

Procedia PDF Downloads 282

Authors: A. Bortkiewcz, A. Dudarewicz, P. Małecki, M. Kłaczyński, T. Wszołek, Małgorzata Pawlaczyk-Łuszczyńska

Abstract:

Low-frequency noise (LFN) has been recognized as a special environmental pollutant. It is usually considered a broadband noise with the dominant content of low frequencies from 10 Hz to 250 Hz. A growing body of data shows that LFN differs in nature from other environmental noises, which are at comparable levels but not dominated by low-frequency components. The primary and most frequent adverse effect of LFN exposure is annoyance. Moreover, some recent investigations showed that LFN at relatively low A-weighted sound pressure levels (40−45 dB) occurring in office-like areas could adversely affect the mental performance, especially of high-sensitive subjects. It is well documented that high-frequency noise disturbs various types of human functions; however, there is very little data on the impact of LFN on well-being and health, including the cardiovascular system. Heart rate variability (HRV) is a sensitive marker of autonomic regulation of the circulatory system. Walker and co-workers found that LFN has a significantly more negative impact on cardiovascular response than exposure to high-frequency noise and that changes in HRV parameters resulting from LFN exposure tend to persist over time. The negative reactions of the cardiovascular system in response to LFN generated by wind turbines (20-200 Hz) were confirmed by Chiu. The scientific aim of the study is to assess the relationship between the spectral-temporal characteristics of LFN and the activity of the autonomic nervous system, considering the subjective assessment of annoyance, sensitivity to this type of noise, and cognitive and general health status. The study will be conducted in 20 male students in a special, acoustically prepared, constantly supervised room. Each person will be tested 4 times (4 sessions), under conditions of non-exposure (sham) and exposure to noise of wind turbines recorded at a distance of 250 meters from the turbine with different frequencies and frequency ranges: acoustic band 20 Hz-20 kHz, infrasound band 5-20 Hz, acoustic band + infrasound band. The order of sessions of the experiment will be randomly selected. Each session will last 1 h. There will be a 2-3 days break between sessions to exclude the possibility of the earlier session influencing the results of the next one. Before the first exposure, a questionnaire will be conducted on noise sensitivity, general health status using the GHQ questionnaire, hearing organ status and sociodemographic data. Before each of the 4 exposures, subjects will complete a brief questionnaire on their mood and sleep quality the night before the test. After the test, the subjects will be asked about any discomfort and subjective symptoms during the exposure. Before the test begins, Holter ECG monitoring equipment will be installed. HRV will be analyzed from the ECG recordings, including time and frequency domain parameters. The tests will always be performed in the morning (9-12) to avoid the influence of diurnal rhythm on HRV results. Students will perform psychological tests 15 minutes before the end of the test (Vienna Test System).

Keywords: neurovegetative control, heart rate variability (HRV), cognitive processes, low frequency noise

Procedia PDF Downloads 80