Search results for: fluorescent sensing probe

Authors: Pola Goldberg Oppenheimer, Stephan Hofmann, Sumeet Mahajan

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Owing to its fingerprint molecular specificity and high sensitivity, surface-enhanced Raman scattering (SERS) is an established analytical tool for chemical and biological sensing capable of single-molecule detection. A strong Raman signal can be generated from SERS-active platforms given the analyte is within the enhanced plasmon field generated near a noble-metal nanostructured substrate. The key requirement for generating strong plasmon resonances to provide this electromagnetic enhancement is an appropriate metal surface roughness. Controlling nanoscale features for generating these regions of high electromagnetic enhancement, the so-called SERS ‘hot-spots’, is still a challenge. Significant advances have been made in SERS research, with wide-ranging techniques to generate substrates with tunable size and shape of the nanoscale roughness features. Nevertheless, the development and application of SERS has been inhibited by the irreproducibility and complexity of fabrication routes. The ability to generate straightforward, cost-effective, multiplex-able and addressable SERS substrates with high enhancements is of profound interest for miniaturised sensing devices. Carbon nanotubes (CNTs) have been concurrently, a topic of extensive research however, their applications for plasmonics has been only recently beginning to gain interest. CNTs can provide low-cost, large-active-area patternable substrates which, coupled with appropriate functionalization capable to provide advanced SERS-platforms. Herein, advanced methods to generate CNT-based SERS active detection platforms will be discussed. First, a novel electrohydrodynamic (EHD) lithographic technique will be introduced for patterning CNT-polymer composites, providing a straightforward, single-step approach for generating high-fidelity sub-micron-sized nanocomposite structures within which anisotropic CNTs are vertically aligned. The created structures are readily fine-tuned, which is an important requirement for optimizing SERS to obtain the highest enhancements with each of the EHD-CNTs individual structural units functioning as an isolated sensor. Further, gold-functionalized VACNTFs are fabricated as SERS micro-platforms. The dependence on the VACNTs’ diameters and density play an important role in the Raman signal strength, thus highlighting the importance of structural parameters, previously overlooked in designing and fabricating optimized CNTs-based SERS nanoprobes. VACNTs forests patterned into predesigned pillar structures are further utilized for multiplex detection of bio-analytes. Since CNTs exhibit electrical conductivity and unique adsorption properties, these are further harnessed in the development of novel chemical and bio-sensing platforms.

Keywords: carbon nanotubes (CNTs), EHD patterning, SERS, vertically aligned carbon nanotube forests (VACNTF)

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Authors: Neha Gupta

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Landslide vulnerability is considered as the crucial parameter for the assessment of landslide risk. The term vulnerability defined as the damage or degree of elements at risk of different dimensions, i.e., physical, social, economic, and environmental dimensions. Himalaya region is very prone to multi-hazard such as floods, forest fires, earthquakes, and landslides. With the increases in fatalities rates, loss of infrastructure, and economy due to landslide in the Himalaya region, leads to the assessment of vulnerability. In this study, a methodology to measure the combination of vulnerability dimension, i.e., social vulnerability, physical vulnerability, and environmental vulnerability in one framework. A combined result of these vulnerabilities has rarely been carried out. But no such approach was applied in the Indian Scenario. The methodology was applied in an area of east Sikkim Himalaya, India. The physical vulnerability comprises of building footprint layer extracted from remote sensing data and Google Earth imaginary. The social vulnerability was assessed by using population density based on land use. The land use map was derived from a high-resolution satellite image, and for environment vulnerability assessment NDVI, forest, agriculture land, distance from the river were assessed from remote sensing and DEM. The classes of social vulnerability, physical vulnerability, and environment vulnerability were normalized at the scale of 0 (no loss) to 1 (loss) to get the homogenous dataset. Then the Multi-Criteria Analysis (MCA) was used to assign individual weights to each dimension and then integrate it into one frame. The final vulnerability was further classified into four classes from very low to very high.

Keywords: landslide, multi-criteria analysis, MCA, physical vulnerability, social vulnerability

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Authors: Deepak Khare, Radha Krishan, Bhaskar Nikam

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The present study deals with the results of the Ortho-rectified Cartosat-1 PAN (2.5 m resolution) satellite data analysis for the extraction of canal networks under the Eastern Ganga Canal (EGC) command. Based on the information derived through the remote sensing data, in terms of the number of canals, their physical status and hydraulic connectivity from the source, irrigation potential (IP) created in the command was assessed by comparing with planned/design canal-wise irrigation potentials. All the geospatial information generated in the study is organized in a geodatabase. The EGC project irrigates the command through one main canal, five branch canals, 36 distributaries and 186 minors. The study was conducted with the main objectives of inventory and mapping of irrigation infrastructure using geographic information system (GIS), remote sensing and field data. Likewise, the assessment of irrigation potential created using the mapped infrastructure was performed as on March 2017. Results revealed that the canals were not only pending but were also having gap/s, and hydraulically disconnected in each branch canal and also in minors of EGC. A total of 16622.3 ha of commands were left untouched with canal water just due to the presence of gaps in the EGC project. The sum of all the gaps present in minor canals was 11.92 km, while in distributary, it was 2.63 km. This is a very good scenario that balances IP can be achieved by working on the gaps present in minor canals. Filling the gaps in minor canals can bring most of the area under irrigation, especially the tail reaches command.

Keywords: canal command, GIS, hydraulic connectivity, irrigation potential

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Authors: Hui Zhang, Sherif Beskhyroun

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In this study, a highly flexible LoRa-Based wireless sensing system was used to assess the strain state performance of building structures. The system was developed to address the local damage limitation of structural health monitoring (SHM) systems. The system is part of an intelligent SHM system designed to monitor, collect and transmit strain changes in key structural components. The main purpose of the wireless sensor system is to reduce the development and installation costs, and reduce the power consumption of the system, so as to achieve long-time monitoring. The highly stretchable flexible strain gauge is mounted on the surface of the structure and is waterproof, heat resistant, and low temperature resistant, greatly reducing the installation and maintenance costs of the sensor. The system was also developed with the aim of using LoRa wireless communication technology to achieve both low power consumption and long-distance transmission, therefore solving the problem of large-scale deployment of sensors to cover more areas in large structures. In the long-term monitoring of the building structure, the system shows very high performance, very low actual power consumption, and wireless transmission stability. The results show that the developed system has a high resolution, sensitivity, and high possibility of long-term monitoring.

Keywords: LoRa, SHM system, strain measurement, civil structures, flexible sensing system

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Authors: Simona Dostalova, Pavel Kopel, Marketa Vaculovicova, Vojtech Adam, Rene Kizek

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Protein apoferritin seems to be a very promising structure for use as a nanocarrier. It is prepared from intracellular ferritin protein naturally found in most organisms. The role of ferritin proteins is to store and transport ferrous ions. Apoferritin is a hollow protein cage without ferrous ions that can be prepared from ferritin by reduction with thioglycolic acid or dithionite. The structure of apoferritin is composed of 24 protein subunits, creating a sphere with 12 nm in diameter. The inner cavity has a diameter of 8 nm. The drug encapsulation process is based on the response of apoferritin structure to the pH changes of surrounding solution. In low pH, apoferritin is disassembled into individual subunits and its structure is “opened”. It can then be mixed with any desired cytotoxic drug and after adjustment of pH back to neutral the subunits are reconnected again and the drug is encapsulated within the apoferritin particles. Excess drug molecules can be removed by dialysis. The receptors for apoferritin, SCARA5 and TfR1 can be found in the membrane of both healthy and cancer cells. To enhance the specific targeting of apoferritin nanocarrier, it is possible to modify its surface with targeting moieties, such as antibodies. To ensure sterically correct complex, we used a a peptide linker based on a protein G with N-terminus affinity towards Fc region of antibodies. To connect the peptide to the surface of apoferritin, the C-terminus of peptide was made of cysteine with affinity to gold. The surface of apoferritin with encapsulated doxorubicin (ApoDox) was coated either with gold nanoparticles (ApoDox-Nano) or gold (III) chloride hydrate reduced with sodium borohydride (ApoDox-HAu). The applied amount of gold in form of gold (III) chloride hydrate was 10 times higher than in the case of gold nanoparticles. However, after removal of the excess unbound ions by electrophoretic separation, the concentration of gold on the surface of apoferritin was only 6 times higher for ApoDox-HAu in comparison with ApoDox-Nano. Moreover, the reduction with sodium borohydride caused a loss of doxorubicin fluorescent properties (excitation maximum at 480 nm with emission maximum at 600 nm) and thus its biological activity. Fluorescent properties of ApoDox-Nano were similar to the unmodified ApoDox, therefore it was more suited for the intended use. To evaluate the specificity of apoferritin modified with antibodies, we used ELISA-like method with the surface of microtitration plate wells coated by the antigen (goat anti-human IgG antibodies). To these wells, we applied ApoDox without targeting antibodies and ApoDox-Nano modified with targeting antibodies (human IgG antibodies). The amount of unmodified ApoDox on antigen after incubation and subsequent rinsing with water was 5 times lower than in the case of ApoDox-Nano modified with targeting antibodies. The modification of non-gold ApoDox with antibodies caused no change in its targeting properties. It can therefore be concluded that the demonstrated procedure allows us to create nanocarrier with enhanced targeting properties, suitable for nanomedicine.

Keywords: apoferritin, doxorubicin, nanocarrier, targeting antibodies

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Authors: Shreekumari Patel, Prabhjot Kaur, Paras Solanki

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Moon Mineralogy Mapper (M3), Miniature Radio Frequency (Mini-RF), Kaguya Terrain Camera images, Lunar Orbiter Laser Altimeter (LOLA) digital elevation model (DEM) and Lunar Reconnaissance Orbiter Camera (LROC)- Narrow angle camera (NAC) and Wide angle camera (WAC) images were used to study mineralogy, surface physical properties, and age of the 42 km diameter Kopff crater. M3 indicates the low albedo crater floor to be high-Ca pyroxene dominated associated with floor fracture suggesting the igneous activity of the gabbroic material. Signature of anorthositic material is sampled on the eastern edge as target material is excavated from ~3 km diameter impact crater providing access to the crustal composition. Several occurrences of spinel were detected in northwestern rugged terrain. Our observation can be explained by exposure of spinel by this crater that impacted onto the inner rings of Orientale basin. Spinel was part of the pre-impact target, an intrinsic unit of basin ring. Crater floor was dated by crater counts performed on Kaguya TC images. Nature of surface was studied in detail with LROC NAC and Mini-RF. Freshly exposed surface and boulder or debris seen in LROC NAC images have enhanced radar signal in comparison to mature terrain of Kopff crater. This multidisciplinary analysis of remote sensing data helps to assess lunar surface in detail.

Keywords: crater, mineralogy, moon, radar observations

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Authors: Lorenzo Gontrani, Marilena Carbone, Domenica Tommasa Donia, Elvira Maria Bauer, Pietro Tagliatesta

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One of the fields where DES shows remarkable added values is the synthesis Of inorganic materials, in particular nanoparticles. In this field, the higher- ent and highly-tunable nano-homogeneities of DES structure give origin to a marked templating effect, a precious role that has led to the recent bloom of a vast number of studies exploiting these new synthesis media to prepare Nanomaterials and composite structures of various kinds. In this contribution, the most recent developments in the field will be reviewed, and some ex-citing examples of novel metal oxide nanoparticles syntheses using non-toxic type-IV Deep Eutectic Solvents will be described. The prepared materials possess nanometric dimensions and show flower-like shapes. The use of the pre- pared nanoparticles as fluorescent materials for the detection of various contaminants is under development.

Keywords: metal deep eutectic solvents, nanoparticles, inorganic synthesis, type IV DES, lamellar

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Authors: Jung Park, Anca Mazare, Klaus Von Der Mark, Patrik Schmuki

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In clinical application of TiO2 implants on tooth and hip replacement, migration, adhesion and differentiation of neighboring mesenchymal stem cells onto implant surfaces are critical steps for successful bone regeneration. In a recent decade, accumulated attention has been paid on nanoscale electrochemical surface modifications on TiO2 layer for improving bone-TiO2 surface integration. We generated, on titanium surfaces, self-assembled layers of vertically oriented TiO2 nanotubes with defined diameters between 15 and 100 nm and here we show that mesenchymal stem cells finely sense TiO2 nanotubular geometry and quickly decide their cell fate either to differentiation into osteoblasts or to programmed cell death (apoptosis) on TiO2 nanotube layers. These cell fate decisions are critically dependent on nanotube size differences (15-100nm in diameters) of TiO2 nanotubes sensing by integrin clustering. We further demonstrate that nanoscale topography-sensing is feasible not only in mesenchymal stem cells but rather seems as generalized nanoscale microenvironment-cell interaction mechanism in several cell types composing bone tissue network including osteoblasts, osteoclast, endothelial cells and hematopoietic stem cells. Additionally we discuss the synergistic effect of simultaneous stimulation by nanotube-bound growth factor and nanoscale topographic cues on enhanced bone regeneration.

Keywords: TiO2 nanotube, stem cell fate decision, nano-scale microenvironment, bone regeneration

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Authors: Zahid Rehman, TorOve Leiknes

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Quorum sensing (QS) is the process by which bacteria communicate with each other through small signaling molecules, such as N-acylhomoserine lactones (AHLs). Also, certain bacteria have the ability to degrade AHL molecules by a process referred to as quorum quenching (QQ); therefore, QQ can be used to control bacterial infections and biofilm formation. In this study, we aimed to identify new species of bacteria with QQ activities. To achieve this, sediments from Red Sea were collected either in the close vicinity of Sea grass or from area with no vegetation. From these samples, we isolated 72 bacterial strains and tested their ability to degrade/inactivate AHL molecules. Chromobacterium violaceum based bioassay was used in initial screening of isolates for QQ activity. The QQ activity of the positive isolates was further confirmed and quantified by employing liquid chromatography and mass spectrometry. These analyses showed that isolated bacterial strain could degrade AHL molecules with different acyl chain length and modifications. Sequencing of 16S-rRNA genes of positive isolates revealed that they belong to three different genera. Specifically, two isolates belong to genus Erythrobacter, four to Labrenzia and one isolate belongs to Bacterioplanes. Time course experiment showed that isolate belonging to genus Erythrobacter could degrade AHLs faster than other isolates. Furthermore, these isolates were tested for their ability to inhibit formation of biofilm and degradation of 3OXO-C12 AHLs produced by P. aeruginosa PAO1. Our results showed that isolate VG12 is better at controlling biofilm formation. This aligns with the ability of VG12 to cause at least 10-fold reduction in the amount of different AHLs tested.

Keywords: quorum sensing, biofilm, quorum quenching, anti-biofouling

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Authors: Nadeem Qaiser, Sherjeel Munsif Khan, Muhammad Mustafa Hussian, Vincent Tung

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One of the emerging fields in the detection of chronic diseases is based on the point-of-care (POC) early monitoring of the symptoms and thus provides a state-of-the-art personalized healthcare system. Nowadays, wearable and flexible sensors are being used for analyzing sweat, glucose, blood pressure, and other skin conditions. However, localized jaw-bone swelling called parotid-swelling caused by some viruses has never been tracked before. To track physical motion or deformations, strain sensors, especially piezoresistive ones, are widely used. This work, for the first time, reports carbon nanotubes (CNTs)-based piezoresistive sensing patch that is highly flexible and stretchable and can record muscle deformations in real-time. The developed patch offers an excellent gauge factor for in-plane stretching and spatial expansion with low hysteresis. To calibrate the volumetric muscle expansion, we fabricated the pneumatic actuator that experienced volumetric expansion and thus redefined the gauge factor. Moreover, we employ a Bluetooth-low-energy system that can send information about muscle activity in real-time to a smartphone app. We utilized COMSOL calculations to reveal the mechanical robustness of the patch. The experiments showed the sensing patch's greater cyclability, making it a patch for personal healthcare and an excellent choice for monitoring the real-time POC monitoring of the human muscle swelling.

Keywords: piezoresistive strain sensor, FEM simulations, CNTs sensor, flexible

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Authors: Bernabeo R. Alberto

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Unmanned aerial vehicles (UAV) platforms or remotely piloted aircraft system (Rpas) - with dedicated sensors - are fundamental support to the planning, running, and control of the territory in which public safety is or may be at risk for post-disaster assessments such as flooding or landslides, for searching lost people, for crime and accident scene photography, for assisting traffic control at major events, for teaching geography, history, natural science and all those subjects that require a continuous cyclical process of observation, evaluation and interpretation. Through the use of proximal remote sensing information related to anthropic landscape and nature integration, there is an opportunity to improve knowledge and management decision-making for the safeguarding of the environment, for farming, wildlife management, land management, mapping, glacier monitoring, atmospheric monitoring, for the conservation of archeological, historical, artistic and architectural sites, allowing an exact delimitation of the site in the territory. This paper will go over many different mission types. Within each mission type, it will give a broad overview to familiarize the reader but not make them an expert. It will also give detailed information on the payloads and other testing parameters the Unmanned Aerial Vehicles (UAV) use to complete a mission. The project's goal is to improve satellite maps about the stress of the plants, air quality monitoring, and related health issues.

Keywords: proximal remote sensing, remotely piloted aircraft system, risk, safety, unmanned aerial vehicle

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Authors: Eiman Kattan, Hong Wei

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In using Convolutional Neural Network (CNN) for classification, there is a set of hyperparameters available for the configuration purpose. This study aims to evaluate the impact of a range of parameters in CNN architecture i.e. AlexNet on land cover classification based on four remotely sensed datasets. The evaluation tests the influence of a set of hyperparameters on the classification performance. The parameters concerned are epoch values, batch size, and convolutional filter size against input image size. Thus, a set of experiments were conducted to specify the effectiveness of the selected parameters using two implementing approaches, named pertained and fine-tuned. We first explore the number of epochs under several selected batch size values (32, 64, 128 and 200). The impact of kernel size of convolutional filters (1, 3, 5, 7, 10, 15, 20, 25 and 30) was evaluated against the image size under testing (64, 96, 128, 180 and 224), which gave us insight of the relationship between the size of convolutional filters and image size. To generalise the validation, four remote sensing datasets, AID, RSD, UCMerced and RSCCN, which have different land covers and are publicly available, were used in the experiments. These datasets have a wide diversity of input data, such as number of classes, amount of labelled data, and texture patterns. A specifically designed interactive deep learning GPU training platform for image classification (Nvidia Digit) was employed in the experiments. It has shown efficiency in both training and testing. The results have shown that increasing the number of epochs leads to a higher accuracy rate, as expected. However, the convergence state is highly related to datasets. For the batch size evaluation, it has shown that a larger batch size slightly decreases the classification accuracy compared to a small batch size. For example, selecting the value 32 as the batch size on the RSCCN dataset achieves the accuracy rate of 90.34 % at the 11th epoch while decreasing the epoch value to one makes the accuracy rate drop to 74%. On the other extreme, setting an increased value of batch size to 200 decreases the accuracy rate at the 11th epoch is 86.5%, and 63% when using one epoch only. On the other hand, selecting the kernel size is loosely related to data set. From a practical point of view, the filter size 20 produces 70.4286%. The last performed image size experiment shows a dependency in the accuracy improvement. However, an expensive performance gain had been noticed. The represented conclusion opens the opportunities toward a better classification performance in various applications such as planetary remote sensing.

Keywords: CNNs, hyperparamters, remote sensing, land cover, land use

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Authors: Khalid Hussein, Waleed Abdalati, Pakorn Petchprayoon, Khaula Alkaabi

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In this study, we integrated ASTER thermal data with an area-based spatial insolation model to identify and delineate geothermally active areas in Yellowstone National Park (YNP). Two pairs of L1B ASTER day- and nighttime scenes were used to calculate land surface temperature. We employed the Emissivity Normalization Algorithm which separates temperature from emissivity to calculate surface temperature. We calculated the incoming solar radiation for the area covered by each of the four ASTER scenes using an insolation model and used this information to compute temperature due to solar radiation. We then identified the statistical thermal anomalies using land surface temperature and the residuals calculated from modeled temperatures and ASTER-derived surface temperatures. Areas that had temperatures or temperature residuals greater than 2σ and between 1σ and 2σ were considered ASTER-modeled thermal anomalies. The areas identified as thermal anomalies were in strong agreement with the thermal areas obtained from the YNP GIS database. Also the YNP hot springs and geysers were located within areas identified as anomalous thermal areas. The consistency between our results and known geothermally active areas indicate that thermal remote sensing data, integrated with a spatial-based insolation model, provides an effective means for identifying and locating areas of geothermal activities over large areas and rough terrain.

Keywords: thermal remote sensing, insolation model, land surface temperature, geothermal anomalies

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Authors: Nubwimana Rachel, Mugabowindekwe Maurice

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Trees play a crucial role in maintaining biodiversity and providing various ecological services. Traditional methods of counting trees are time-consuming, and there is a need for more efficient techniques. However, deep learning makes it feasible to identify the multi-scale elements hidden in aerial imagery. This research focuses on the application of deep learning techniques for tree detection and counting in both forest and non-forest areas through the exploration of the deep learning application for automated tree detection and counting using satellite imagery. The objective is to identify the most effective model for automated tree counting. We used different deep learning models such as YOLOV7, SSD, and UNET, along with Generative Adversarial Networks to generate synthetic samples for training and other augmentation techniques, including Random Resized Crop, AutoAugment, and Linear Contrast Enhancement. These models were trained and fine-tuned using satellite imagery to identify and count trees. The performance of the models was assessed through multiple trials; after training and fine-tuning the models, UNET demonstrated the best performance with a validation loss of 0.1211, validation accuracy of 0.9509, and validation precision of 0.9799. This research showcases the success of deep learning in accurate tree counting through remote sensing, particularly with the UNET model. It represents a significant contribution to the field by offering an efficient and precise alternative to conventional tree-counting methods.

Keywords: remote sensing, deep learning, tree counting, image segmentation, object detection, visualization

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Authors: Alena Cejkova, Martina Paldrychova, Jana Michailidu, Olga Matatkova, Jan Masak

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Increasing the resistance of pathogenic microorganisms to many antibiotics is a serious threat to the treatment of infectious diseases and cleaning medical instruments. It should be added that the resistance of microbial populations growing in biofilms is often up to 1000 times higher compared to planktonic cells. Biofilm formation in a number of microorganisms is largely influenced by the quorum sensing regulatory mechanism. Finding external factors such as natural substances or physical processes that can interfere effectively with quorum sensing signal molecules should reduce the ability of the cell population to form biofilm and increase the effectiveness of antibiotics. The present work is devoted to the effect of chitosan as a representative of natural substances with anti-biofilm activity and non- thermal plasma (NTP) alone or in combination with polymyxin B on biofilm formation of Pseudomonas aeruginosa. Particular attention was paid to the influence of these agents on the level of quorum sensing signal molecules (acyl-homoserine lactones) during planktonic and biofilm cultivations. Opportunistic pathogenic strains of Pseudomonas aeruginosa (DBM 3081, DBM 3777, ATCC 10145, ATCC 15442) were used as model microorganisms. Cultivations of planktonic and biofilm populations in 96-well microtiter plates on horizontal shaker were used for determination of antibiotic and anti-biofilm activity of chitosan and polymyxin B. Biofilm-growing cells on titanium alloy, which is used for preparation of joint replacement, were exposed to non-thermal plasma generated by cometary corona with a metallic grid for 15 and 30 minutes. Cultivation followed in fresh LB medium with or without chitosan or polymyxin B for next 24 h. Biofilms were quantified by crystal violet assay. Metabolic activity of the cells in biofilm was measured using MTT (3-[4,5-dimethylthiazol-2-yl]-2,5 diphenyl tetrazolium bromide) colorimetric test based on the reduction of MTT into formazan by the dehydrogenase system of living cells. Activity of N-acyl homoserine lactones (AHLs) compounds involved in the regulation of biofilm formation was determined using Agrobacterium tumefaciens strain harboring a traG::lacZ/traR reporter gene responsive to AHLs. The experiments showed that both chitosan and non-thermal plasma reduce the AHLs level and thus the biofilm formation and stability. The effectiveness of both agents was somewhat strain dependent. During the eradication of P. aeruginosa DBM 3081 biofilm on titanium alloy induced by chitosan (45 mg / l) there was an 80% decrease in AHLs. Applying chitosan or NTP on the P. aeruginosa DBM 3777 biofilm did not cause a significant decrease in AHLs, however, in combination with both (chitosan 55 mg / l and NTP 30 min), resulted in a 70% decrease in AHLs. Combined application of NTP and polymyxin B allowed reduce antibiotic concentration to achieve the same level of AHLs inhibition in P. aeruginosa ATCC 15442. The results shown that non-thermal plasma and chitosan have considerable potential for the eradication of highly resistant P. aeruginosa biofilms, for example on medical instruments or joint implants.

Keywords: anti-biofilm activity, chitosan, non-thermal plasma, opportunistic pathogens

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Authors: Tatsuya Takino, Izuru Nomura, Yuji Kageyama, Shin Nagata, Hiroyuki Kamata

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We propose a method of detecting the craters from the image of the lunar surface. This proposal assumes that it is applied to SLIM (Smart Lander for Investigating Moon) working group aiming at the pinpoint landing on the lunar surface and investigating scientific research. It is difficult to equip and use high-performance computers for the small space probe. So, it is necessary to use a small computer with an exclusive hardware such as FPGA. We have studied the crater detection using principal component analysis (PCA), In this paper, We implement detection algorithm into the FPGA, and the detection is performed on the data that was captured from the CMOS camera.

Keywords: crater detection, PCA, FPGA, image processing

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Authors: J. Lyagaeva, D. Medvedev, A. Brouzgou, A. Demin, P. Tsiakaras

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The investigation of highly conductive and chemically stable electrolytes for solid oxide fuel cells (SOFC) is a necessity. The aim of the present work is to study the influence of acceptor dopant on the functional properties of textured BaCe0.5Zr0.3Ln0.2O3−δ (Ln = Yb, Y, Gd, Sm, Nd) ceramics. The X-Ray diffraction analysis, scanning electron microscopy, dilatometry and 4-probe dc method of conductivity measurements were used. It was found that the mean grain size of ceramics increases (from 1.4 to 3.2 μm), thermal expansion coefficient grows (from 7.6•10–6 to 10.7•10–6 К–1), but ionic conductivity decreases (from 14 to 3 mS cm–1 at 900°С), when ionic radii of impurity acceptor increases from 0.868 Å (Yb3+) to 0.983 Å (Nd3+).

Keywords: acceptor dopant, crystal structure, proton-conducting, SOFC

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Authors: Eugene Y. J. Aw, J. W. Koh, S. H. Chew, K. E. Chua, Lionel L. J. Ang, Algernon C. S. Hong, Danette S. E. Tan, Grace H. B. Foo, K. Q. Hong, L. M. Cheng, M. L. Leong

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This paper presents a novel rapid soil classification technique that combines computer vision with four-probe soil electrical resistivity method and cone penetration test (CPT), to improve the accuracy and productivity of on-site classification of excavated soil. In Singapore, excavated soils from local construction projects are transported to Staging Grounds (SGs) to be reused as fill material for land reclamation. Excavated soils are mainly categorized into two groups (“Good Earth” and “Soft Clay”) based on particle size distribution (PSD) and water content (w) from soil investigation reports and on-site visual survey, such that proper treatment and usage can be exercised. However, this process is time-consuming and labour-intensive. Thus, a rapid classification method is needed at the SGs. Computer vision, four-probe soil electrical resistivity and CPT were combined into an innovative non-destructive and instantaneous classification method for this purpose. The computer vision technique comprises soil image acquisition using industrial grade camera; image processing and analysis via calculation of Grey Level Co-occurrence Matrix (GLCM) textural parameters; and decision-making using an Artificial Neural Network (ANN). Complementing the computer vision technique, the apparent electrical resistivity of soil (ρ) is measured using a set of four probes arranged in Wenner’s array. It was found from the previous study that the ANN model coupled with ρ can classify soils into “Good Earth” and “Soft Clay” in less than a minute, with an accuracy of 85% based on selected representative soil images. To further improve the technique, the soil strength is measured using a modified mini cone penetrometer, and w is measured using a set of time-domain reflectometry (TDR) probes. Laboratory proof-of-concept was conducted through a series of seven tests with three types of soils – “Good Earth”, “Soft Clay” and an even mix of the two. Validation was performed against the PSD and w of each soil type obtained from conventional laboratory tests. The results show that ρ, w and CPT measurements can be collectively analyzed to classify soils into “Good Earth” or “Soft Clay”. It is also found that these parameters can be integrated with the computer vision technique on-site to complete the rapid soil classification in less than three minutes.

Keywords: Computer vision technique, cone penetration test, electrical resistivity, rapid and non-destructive, soil classification

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Authors: Ankit Tyagi, Reet Kamal Tiwari, Naveen James

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Landslide is the major geo-environmental problem of Himalaya because of high ridges, steep slopes, deep valleys, and complex system of streams. They are mainly triggered by rainfall and earthquake and causing severe damage to life and property. In Uttarakhand, the Tehri reservoir rim area, which is situated in the lesser Himalaya of Garhwal hills, was selected for landslide hazard zonation (LHZ). The study utilized different types of data, including geological maps, topographic maps from the survey of India, Landsat 8, and Cartosat DEM data. This paper presents the use of a weighted overlay method in LHZ using fourteen causative factors. The various data layers generated and co-registered were slope, aspect, relative relief, soil cover, intensity of rainfall, seismic ground shaking, seismic amplification at surface level, lithology, land use/land cover (LULC), normalized difference vegetation index (NDVI), topographic wetness index (TWI), stream power index (SPI), drainage buffer and reservoir buffer. Seismic analysis is performed using peak horizontal acceleration (PHA) intensity and amplification factors in the evaluation of the landslide hazard index (LHI). Several digital image processing techniques such as topographic correction, NDVI, and supervised classification were widely used in the process of terrain factor extraction. Lithological features, LULC, drainage pattern, lineaments, and structural features are extracted using digital image processing techniques. Colour, tones, topography, and stream drainage pattern from the imageries are used to analyse geological features. Slope map, aspect map, relative relief are created by using Cartosat DEM data. DEM data is also used for the detailed drainage analysis, which includes TWI, SPI, drainage buffer, and reservoir buffer. In the weighted overlay method, the comparative importance of several causative factors obtained from experience. In this method, after multiplying the influence factor with the corresponding rating of a particular class, it is reclassified, and the LHZ map is prepared. Further, based on the land-use map developed from remote sensing images, a landslide vulnerability study for the study area is carried out and presented in this paper.

Keywords: weighted overlay method, GIS, landslide hazard zonation, remote sensing

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Authors: Suresh Kumar Bandooni, Mirana Laishram

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The Mid Himalaya of Garhwal Himalaya in Uttarakhand (India) has a complex Physiographic features withdiversified climatic conditions and therefore it is suspect to environmental vulnerability. Thenatural disasters and also anthropogenic activities accelerate the rate of environmental vulnerability. To analyse the environmental vulnerability, we have used geoinformatics technologies and numerical models and it is adoptedby using Spatial Principal Component Analysis (SPCA). The model consist of many factors such as slope, landuse/landcover, soil, forest fire risk, landslide susceptibility zone, human population density and vegetation index. From this model, the environmental vulnerability integrated index (EVSI) is calculated for Pasol Gad Watershed of Garhwal Himalaya for the years 1987, 2000, and 2013 and the Vulnerability is classified into five levelsi.e. Very low, low, medium, high and very highby means of cluster principle. The resultsforeco-environmental vulnerability distribution in study area shows that medium, high and very high levels are dominating in the area and it is mainly caused by the anthropogenic activities and natural disasters. Therefore, proper management forconservation of resources is utmost necessity of present century. It is strongly believed that participation at community level along with social worker, institutions and Non-governmental organization (NGOs) have become a must to conserve and protect the environment.

Keywords: eco-environment vulnerability, spatial principal component analysis, remote sensing, geographic information system, institutions, Himalaya

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Authors: Guanhua Zhou, Zhongqi Ma

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Submerged aquatic vegetation (SAV) in wetlands can absorb nitrogen and phosphorus effectively to prevent the eutrophication of water. It is feasible to monitor the distribution of SAV through remote sensing, but for the reason of weak vegetation signals affected by water body, traditional terrestrial vegetation indices are not applicable. This paper aims at constructing SAV index to enhance the vegetation signals and distinguish SAV from water body. The methodology is as follows: (1) select the bands sensitive to the vegetation parameters based on global sensitivity analysis of SAV canopy radiative transfer model; (2) take the soil line concept as reference, analyze the distribution of SAV and water reflectance simulated by SAV canopy model and semi-analytical water model in the two-dimensional space built by different sensitive bands; (3)select the band combinations which have better separation performance between SAV and water, and use them to build the SAVI indices in the form of normalized difference vegetation index(NDVI); (4)analyze the sensitivity of indices to the water and vegetation parameters, choose the one more sensitive to vegetation parameters. It is proved that index formed of the bands with central wavelengths in 705nm and 842nm has high sensitivity to chlorophyll content in leaves while it is less affected by water constituents. The model simulation shows a general negative, little correlation of SAV index with increasing water depth. Moreover, the index enhances capabilities in separating SAV from water compared to NDVI. The SAV index is expected to have potential in parameter inversion of wetland remote sensing.

Keywords: global sensitivity analysis, radiative transfer model, submerged aquatic vegetation, vegetation indices

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Authors: Joel Ballesteros, Harriet Jane Caleja, Florian Del Mundo, Cherrie Pascual

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Diffraction-based sensing was utilized in the quantification of human ferritin in blood serum to provide an alternative to label-based immunoassays currently used in clinical diagnostics and researches. The diffraction intensity was measured by the diffractive optics technology or dotLab™ system. Two methods were evaluated in this study: direct immunoassay and direct sandwich immunoassay. In the direct immunoassay, human ferritin was captured by human ferritin antibodies immobilized on an avidin-coated sensor while the direct sandwich immunoassay had an additional step for the binding of a detector human ferritin antibody on the analyte complex. Both methods were repeatable with coefficient of variation values below 15%. The direct sandwich immunoassay had a linear response from 10 to 500 ng/mL which is wider than the 100-500 ng/mL of the direct immunoassay. The direct sandwich immunoassay also has a higher calibration sensitivity with value 0.002 Diffractive Intensity (ng mL-1)-1) compared to the 0.004 Diffractive Intensity (ng mL-1)-1 of the direct immunoassay. The limit of detection and limit of quantification values of the direct immunoassay were found to be 29 ng/mL and 98 ng/mL, respectively, while the direct sandwich immunoassay has a limit of detection (LOD) of 2.5 ng/mL and a limit of quantification (LOQ) of 8.2 ng/mL. In terms of accuracy, the direct immunoassay had a percent recovery of 88.8-93.0% in PBS while the direct sandwich immunoassay had 94.1 to 97.2%. Based on the results, the direct sandwich immunoassay is a better diffraction-based immunoassay in terms of accuracy, LOD, LOQ, linear range, and sensitivity. The direct sandwich immunoassay was utilized in the determination of human ferritin in blood serum and the results are validated by Chemiluminescent Magnetic Immunoassay (CMIA). The calculated Pearson correlation coefficient was 0.995 and the p-values of the paired-sample t-test were less than 0.5 which show that the results of the direct sandwich immunoassay was comparable to that of CMIA and could be utilized as an alternative analytical method.

Keywords: biosensor, diffraction, ferritin, immunoassay

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Authors: Rodrigo T. Sepulveda-Hirose, Ana B. Carrera-Aguilar, Magnolia G. Martinez-Rivera, Pablo de J. Angeles-Salto, Carlos Herrera-Ventosa

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In order to diminish health risks, it is of major importance to monitor air quality. However, this process is accompanied by the high costs of physical and human resources. In this context, this research is carried out with the main objective of developing a predictive model for concentrations of inhalable particles (PM10-2.5) using remote sensing. To develop the model, satellite images, mainly from Landsat 8, of the Mexico City’s Metropolitan Area were used. Using historical PM10 and PM2.5 measurements of the RAMA (Automatic Environmental Monitoring Network of Mexico City) and through the processing of the available satellite images, a preliminary model was generated in which it was possible to observe critical opportunity areas that will allow the generation of a robust model. Through the preliminary model applied to the scenes of Mexico City, three areas were identified that cause great interest due to the presumed high concentration of PM; the zones are those that present high plant density, bodies of water and soil without constructions or vegetation. To date, work continues on this line to improve the preliminary model that has been proposed. In addition, a brief analysis was made of six models, presented in articles developed in different parts of the world, this in order to visualize the optimal bands for the generation of a suitable model for Mexico City. It was found that infrared bands have helped to model in other cities, but the effectiveness that these bands could provide for the geographic and climatic conditions of Mexico City is still being evaluated.

Keywords: air quality, modeling pollution, particulate matter, remote sensing

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Authors: Eric Mensah

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The effects of rapid urbanisation of tropical sub-Saharan developing cities on local and global climate are of great concern due to the negative impacts of Urban Heat Island (UHI) effects. The importance of urban parks, vegetative cover and forest reserves in these tropical cities have been undervalued with a rapid degradation and loss of these vegetative covers to urban developments which continue to cause an increase in daily mean temperatures and changes to local climatic conditions. Using Landsat data of the same months and period intervals, the spatial variations of land cover changes, temperature, and vegetation were examined to determine how vegetation improves local temperature and the effects of urbanisation on daily mean temperatures over the past 12 years. The remote sensing techniques of maximum likelihood supervised classification, land surface temperature retrieval technique, and normalised differential vegetation index techniques were used to analyse and create the land use land cover (LULC), land surface temperature (LST), and vegetation and non-vegetation cover maps respectively. Results from the study showed an increase in daily mean temperature by 0.80 °C as a result of rapid increase in urban area by 46.13 sq. km and loss of vegetative cover by 46.24 sq. km between 2005 and 2017. The LST map also shows the existence of UHI within the urban areas of Accra, the potential mitigating effects offered by the existence of forest and vegetative cover as demonstrated by the existence of cool islands around the Achimota ecological forest and University of Ghana botanical gardens areas.

Keywords: land surface temperature, climate, remote sensing, urbanisation

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Authors: Beata Zima, Octavio A. Márquez Reyes, Masoud Mohammadgholiha, Jochen Moll, Luca de Marchi

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This document presents the approach of using compressed sensing in signal encoding and information transferring within a guided wave sensor network, comprised of specially designed frequency steerable acoustic transducers (FSATs). Wave propagation in a damaged plate was simulated using commercial FEM-based software COMSOL. Guided waves were excited by means of FSATs, characterized by the special shape of its electrodes, and modeled using PIC255 piezoelectric material. The special shape of the FSAT, allows for focusing wave energy in a certain direction, accordingly to the frequency components of its actuation signal, which makes available a larger monitored area. The process begins when a FSAT detects and records reflection from damage in the structure, this signal is then encoded and prepared for transmission, using a combined approach, based on Compressed Sensing Matching Pursuit and Quadrature Amplitude Modulation (QAM). After codification of the signal is in binary chars the information is transmitted between the nodes in the network. The message reaches the last node, where it is finally decoded and processed, to be used for damage detection and localization purposes. The main aim of the investigation is to determine the location of detected damage using reconstructed signals. The study demonstrates that the special steerable capabilities of FSATs, not only facilitate the detection of damage but also permit transmitting the damage information to a chosen area in a specific direction of the investigated structure.

Keywords: data compression, ultrasonic communication, guided waves, FEM analysis

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Authors: Liyana Zahid, Mohd Fareq Abd Malek, Ee Meng Cheng, Wei Wen Liu, Yeng Seng Lee, Muhammad Nadeem Iqbal, Fwen Hoon Wee

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One of the parameters that affect the performance of microwave absorbers is the shape of the absorbers. This paper shows the performance (reflection loss) of truncated pyramidal and truncated wedge microwave absorbers in the range frequency between 8.2 to 12.4 GHz (X-Band) in simulation. The material used is sugarcane bagasse (SCB) which is one of the new materials that used to fabricate the microwave absorber. The complex permittivity was measured using Agilent dielectric probe technique. The designs were simulated using CST Microwave Studio Software. The reflection losses between these two shapes were compared.

Keywords: microwave absorber, reflection loss, sugarcane bagasse (SCB), X-Band

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Authors: M. Aboalazayem, Essam A. Gouda, Ahmed M. Moussa, Amr E. Flifl

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Field data collecting is considered one of the most difficult work due to the difficulty of accessing large zones such as large lakes. Also, it is well known that the cost of obtaining field data is very expensive. Remotely monitoring of lake water quality (WQ) provides an economically feasible approach comparing to field data collection. Researchers have shown that lake WQ can be properly monitored via Remote sensing (RS) analyses. Using satellite images as a method of WQ detection provides a realistic technique to measure quality parameters across huge areas. Landsat (LS) data provides full free access to often occurring and repeating satellite photos. This enables researchers to undertake large-scale temporal comparisons of parameters related to lake WQ. Satellite measurements have been extensively utilized to develop algorithms for predicting critical water quality parameters (WQPs). The goal of this paper is to use RS to derive WQ indicators in Aswan High Dam Reservoir (AHDR), which is considered Egypt's primary and strategic reservoir of freshwater. This study focuses on using Landsat8 (L-8) band surface reflectance (SR) observations to predict water-quality characteristics which are limited to Turbidity (TUR), total suspended solids (TSS), and chlorophyll-a (Chl-a). ArcGIS pro is used to retrieve L-8 SR data for the study region. Multiple linear regression analysis was used to derive new correlations between observed optical water-quality indicators in April and L-8 SR which were atmospherically corrected by values of various bands, band ratios, and or combinations. Field measurements taken in the month of May were used to validate WQP obtained from SR data of L-8 Operational Land Imager (OLI) satellite. The findings demonstrate a strong correlation between indicators of WQ and L-8 .For TUR, the best validation correlation with OLI SR bands blue, green, and red, were derived with high values of Coefficient of correlation (R2) and Root Mean Square Error (RMSE) equal 0.96 and 3.1 NTU, respectively. For TSS, Two equations were strongly correlated and verified with band ratios and combinations. A logarithm of the ratio of blue and green SR was determined to be the best performing model with values of R2 and RMSE equal to 0.9861 and 1.84 mg/l, respectively. For Chl-a, eight methods were presented for calculating its value within the study area. A mix of blue, red, shortwave infrared 1(SWR1) and panchromatic SR yielded the greatest validation results with values of R2 and RMSE equal 0.98 and 1.4 mg/l, respectively.

Keywords: remote sensing, landsat 8, nasser lake, water quality

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Authors: Muhammad Bilal Qadir, Danish Umer, Amir Shahzad

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The use of conductive materials in smart and interactive textiles is gaining significant importance for creating value addition, innovation, and functional product development. These products find their potential applications in health monitoring, military, protection, communication, sensing, monitoring, actuation, fashion, and lifestyles. The materials which are most commonly employed in such type of interactive textile include intrinsically conducting polymers, conductive inks, and metallic coating on textile fabrics and inherently conducting metallic fibre yarns. In this study, silver coated polyester filament yarn is explored for the development of multifunctional interactive gloves. The composite yarn was developed by covering the silver coated polyester filament around the polyester spun yarn using hollow spindle technique. The electrical and tensile properties of the yarn were studied. This novel yarn was used to manufacture a smart glove to explore the antibacterial, functional, and interactive properties of the yarn. The change in electrical resistance due to finger movement at different bending positions and antimicrobial properties were studied. This glove was also found useful as an interactive tool to operate the commonly used touch screen devices due to its conductive nature. The yarn can also be used to develop the sensing elements like stretch, strain, and piezoresistive sensors. Such sensor can be effectively used in medical and sports textile for performance monitoring, vital signs monitoring and development of antibacterial textile for healthcare and hygiene.

Keywords: conductive yarn, interactive textiles, piezoresistive sensors, smart gloves

Procedia PDF Downloads 239

Authors: R. Sanchez-Salcedo, N. H. Voelcker

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Currently, low breast milk production in women is one of the leading health complications in infants. Recently, It has been demonstrated that exclusive breastfeeding, especially up to a minimum of 6 months, significantly reduces respiratory and gastrointestinal infections, which are the main causes of death in infants. However, the current data shows that a high percentage of women stop breastfeeding their children because they perceive an inadequate supply of milk, and only 45% of children are breastfeeding under 6 months. It is, therefore, clear the necessity to design and develop a biosensor that is sensitive and selective enough to identify and validate a panel of milk biomarkers that allow the early diagnosis of this condition. In this context, electrochemical biosensors could be a powerful tool for assessing all the requirements in terms of reliability, selectivity, sensitivity, cost efficiency and potential for multiplex detection. Moreover, they are suitable for the development of POC devices and wearable sensors. In this work, we report the development of two types of sensing platforms towards several biomarkers, including miRNAs and hormones present in breast milk and dysregulated in this pathological condition. The first type of sensing platform consists of an enzymatic sensor for the detection of lactose, one of the main components in milk. In this design, we used gold surface as an electrochemical transducer due to the several advantages, such as the variety of strategies available for its rapid and efficient functionalization with bioreceptors or capture molecules. For the second type of sensing platform, nanoporous silicon film (pSi) was chosen as the electrode material for the design of DNA sensors and aptasensors targeting miRNAs and hormones, respectively. pSi matrix offers a large superficial area with an abundance of active sites for the immobilization of bioreceptors and tunable characteristics, which increase the selectivity and specificity, making it an ideal alternative material. The analytical performance of the designed biosensors was not only characterized in buffer but also validated in minimally treated breastmilk samples. We have demonstrated the potential of an electrochemical transducer on pSi and gold surface for monitoring clinically relevant biomarkers associated with the heightened risk of low milk production in women. This approach, in which the nanofabrication techniques and the functionalization methods were optimized to increase the efficacy of the biosensor highly provided a foundation for further research and development of targeted diagnosis strategies.

Keywords: biosensors, electrochemistry, early diagnosis, clinical markers, miRNAs

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Authors: Eugene Y. J. Aw, J. W. Koh, S. H. Chew, K. E. Chua, P. L. Goh, Grace H. B. Foo, M. L. Leong

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This paper presents the evaluation of various soil testing methods such as the four-probe soil electrical resistivity method and cone penetration test (CPT) that can complement a newly developed novel rapid soil classification scheme using computer vision, to improve the accuracy and productivity of on-site classification of excavated soil. In Singapore, excavated soils from the local construction industry are transported to Staging Grounds (SGs) to be reused as fill material for land reclamation. Excavated soils are mainly categorized into two groups (“Good Earth” and “Soft Clay”) based on particle size distribution (PSD) and water content (w) from soil investigation reports and on-site visual survey, such that proper treatment and usage can be exercised. However, this process is time-consuming and labor-intensive. Thus, a rapid classification method is needed at the SGs. Four-probe soil electrical resistivity and CPT were evaluated for their feasibility as suitable additions to the computer vision system to further develop this innovative non-destructive and instantaneous classification method. The computer vision technique comprises soil image acquisition using an industrial-grade camera; image processing and analysis via calculation of Grey Level Co-occurrence Matrix (GLCM) textural parameters; and decision-making using an Artificial Neural Network (ANN). It was found from the previous study that the ANN model coupled with ρ can classify soils into “Good Earth” and “Soft Clay” in less than a minute, with an accuracy of 85% based on selected representative soil images. To further improve the technique, the following three items were targeted to be added onto the computer vision scheme: the apparent electrical resistivity of soil (ρ) measured using a set of four probes arranged in Wenner’s array, the soil strength measured using a modified mini cone penetrometer, and w measured using a set of time-domain reflectometry (TDR) probes. Laboratory proof-of-concept was conducted through a series of seven tests with three types of soils – “Good Earth”, “Soft Clay,” and a mix of the two. Validation was performed against the PSD and w of each soil type obtained from conventional laboratory tests. The results show that ρ, w and CPT measurements can be collectively analyzed to classify soils into “Good Earth” or “Soft Clay” and are feasible as complementing methods to the computer vision system.

Keywords: computer vision technique, cone penetration test, electrical resistivity, rapid and non-destructive, soil classification

Procedia PDF Downloads 235