Search results for: taxonomic resolution

Authors: Mustafa Yorgancılar, Emine Atalay, Necdet Akgün, Ali Topal

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In this study, polymerase chain reaction based Inter-simple sequence repeat (ISSR) from DNA fingerprinting techniques were used to investigate the genetic relationships among barley crossbreed genotypes in Turkey. It is important that selection based on the genetic base in breeding programs via ISSR, in terms of breeding time. 14 ISSR primers generated a total of 97 bands, of which 81 (83.35%) were polymorphic. The highest total resolution power (RP) value was obtained from the F2 (0.53) and M16 (0.51) primers. According to the ISSR result, the genetic similarity index changed between 0.64–095; Lane 3 with Line 6 genotypes were the closest, while Line 36 were the most distant ones. The ISSR markers were found to be promising for assessing genetic diversity in barley crossbreed genotypes.

Keywords: barley, crossbreed, genetic similarity, ISSR

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Authors: E. Vazquez-Santacruz, M. Gamboa-Zuniga

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In this paper, we show a methodology for bodies classification in lying state using HOG descriptors and pressures sensors positioned in a matrix form (14 x 32 sensors) on the surface where bodies lie down. it will be done in real time. Our system is embedded in a care robot that can assist the elderly patient and medical staff around to get a better quality of life in and out of hospitals. Due to current technology a limited number of sensors is used, wich results in low-resolution data array, that will be used as image of 14 x 32 pixels. Our work considers the problem of human posture classification with few information (sensors), applying digital process to expand the original data of the sensors and so get more significant data for the classification, however, this is done with low-cost algorithms to ensure the real-time execution.

Keywords: real-time classification, sensors, robots, health care, elderly patients, artificial intelligence

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Authors: Malika Souada, Juanita Rausch, Benjamin Guinot, Christine Bugajny

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The increase of global commerce and tourism makes the shipping sector an important contributor of atmospheric pollution. Both, airborne particles and gaseous pollutants have negative impact on health and climate. This is especially the case in port cities, due to the proximity of the exposed population to the shipping emissions in addition to other multiple sources of pollution linked to the surrounding urban activity. The objective of this study is to determine the concentrations of fine particles (immission), specifically PM2.5, PM1, PM0.3, BC and sulphates, in a context where maritime passenger traffic plays an important role (port area of Bordeaux centre). The methodology is based on high temporal resolution measurements of pollutants, correlated with meteorological and ship movements data. Particles and gaseous pollutants from seven maritime passenger ships were sampled and analysed during the docking, manoeuvring and berthing phases. The particle mass measurements were supplemented by measurements of the number concentration of ultrafine particles (<300 nm diameter). The different measurement points were chosen by taking into account the local meteorological conditions and by pre-modelling the dispersion of the smoke plumes. The results of the measurement campaign carried out during the summer of 2021 in the port of Bordeaux show that the detection of concentrations of particles emitted by ships proved to be punctual and stealthy. Punctual peaks of ultrafine particle concentration in number (P#/m3) and BC (ng/m3) were measured during the docking phases of the ships, but the concentrations returned to their background level within minutes. However, it appears that the influence of the docking phases does not significantly affect the air quality of Bordeaux centre in terms of mass concentration. Additionally, no clear differences in PM2.5 concentrations between the periods with and without ships at berth were observed. The urban background pollution seems to be mainly dominated by exhaust and non-exhaust road traffic emissions. However, temporal high-resolution measurements suggest a probable emission of gaseous precursors responsible for the formation of secondary aerosols related to the ship activities. This was evidenced by the high values of the PM1/BC and PN/BC ratios, tracers of non-primary particle formation, during periods of ship berthing vs. periods without ships at berth. The research findings from this study provide robust support for port area air quality assessment and source apportionment.

Keywords: characterization, fine particulate matter, harbour air quality, shipping impacts

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Authors: Moung Young Lee, Chul Gyu Song

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Photoacoustic imaging is the imaging technology that combines the optical imaging and ultrasound. This provides the high contrast and resolution due to optical imaging and ultrasound imaging, respectively. We developed the real-time photoacoustic tomography (PAT) system using linear-ultrasound transducer and digital acquisition (DAQ) board. There are two types of algorithm for reconstructing the photoacoustic signal. One is back-projection algorithm, the other is FFT algorithm. Especially, we used the non-uniform FFT algorithm. To evaluate the performance of our system and algorithms, we monitored two wires that stands at interval of 2.89 mm and 0.87 mm. Then, we compared the images reconstructed by algorithms. Finally, we monitored the two hairs crossed and compared between these algorithms.

Keywords: back-projection, image comparison, non-uniform FFT, photoacoustic tomography

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Authors: Khoi A. Nguyen, Rodney A. Stewart, Hong Zhang

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‘Water-related energy’ is energy use which is directly or indirectly influenced by changes to water use. Informatics applying a range of mathematical, statistical and rule-based approaches can be used to reveal important information on demand from the available data provided at second, minute or hourly intervals. This study aims to combine these two concepts to improve the current water end use disaggregation problem through applying a wide range of most advanced pattern recognition techniques to analyse the concurrent high-resolution water-energy consumption data. The obtained results have shown that recognition accuracies of all end-uses have significantly increased, especially for mechanised categories, including clothes washer, dishwasher and evaporative air cooler where over 95% of events were correctly classified.

Keywords: deep learning network, smart metering, water end use, water-energy data

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Authors: Marwa Ragab, Eman El-Kimary

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Chiral separation and analysis of omeprazole and naproxen enantiomers in tablets were achieved using high-performance liquid chromatographic method with diode array detection (HPLC-DAD). Kromasil Cellucoat chiral column was used as a stationary phase for separation and the eluting solvent consisted of hexane, isopropanol and trifluoroacetic acid in a ratio of: 90, 9.9 and 0.1, respectively. The chromatographic system was suitable for the enantiomeric separation and analysis of active isomers of the drugs. Resolution values of 2.17 and 3.84 were obtained after optimization of the chromatographic conditions for omeprazole and naproxen isomers, respectively. The determination of S-isomers of each drug in their dosage form was fully validated.

Keywords: chiral analysis, esomeprazole, S-Naproxen, HPLC-DAD

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Authors: Joel Podgorski, Manouchehr Amini, Annette Johnson, Michael Berg

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One-third of the world’s population relies on groundwater for its drinking water. Natural geogenic arsenic and fluoride contaminate ~10% of wells. Prolonged exposure to high levels of arsenic can result in various internal cancers, while high levels of fluoride are responsible for the development of dental and crippling skeletal fluorosis. In poor urban and rural settings, the provision of drinking water free of geogenic contamination can be a major challenge. In order to efficiently apply limited resources in the testing of wells, water resource managers need to know where geogenically contaminated groundwater is likely to occur. The Groundwater Assessment Platform (GAP) fulfills this need by providing state-of-the-art global arsenic and fluoride contamination hazard maps as well as enabling users to create their own groundwater quality models. The global risk models were produced by logistic regression of arsenic and fluoride measurements using predictor variables of various soil, geological and climate parameters. The maps display the probability of encountering concentrations of arsenic or fluoride exceeding the World Health Organization’s (WHO) stipulated concentration limits of 10 µg/L or 1.5 mg/L, respectively. In addition to a reconsideration of the relevant geochemical settings, these second-generation maps represent a great improvement over the previous risk maps due to a significant increase in data quantity and resolution. For example, there is a 10-fold increase in the number of measured data points, and the resolution of predictor variables is generally 60 times greater. These same predictor variable datasets are available on the GAP platform for visualization as well as for use with a modeling tool. The latter requires that users upload their own concentration measurements and select the predictor variables that they wish to incorporate in their models. In addition, users can upload additional predictor variable datasets either as features or coverages. Such models can represent an improvement over the global models already supplied, since (a) users may be able to use their own, more detailed datasets of measured concentrations and (b) the various processes leading to arsenic and fluoride groundwater contamination can be isolated more effectively on a smaller scale, thereby resulting in a more accurate model. All maps, including user-created risk models, can be downloaded as PDFs. There is also the option to share data in a secure environment as well as the possibility to collaborate in a secure environment through the creation of communities. In summary, GAP provides users with the means to reliably and efficiently produce models specific to their region of interest by making available the latest datasets of predictor variables along with the necessary modeling infrastructure.

Keywords: arsenic, fluoride, groundwater contamination, logistic regression

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Authors: K. Daoudi, Z. Othmen, S. El Helali, M.Oueslati, M. Oumezzine

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La0.7Sr0.3CoO3 thin films have been epitaxially grown on LaAlO3 and SrTiO3 (001) single-crystal substrates by metal organic deposition process. The structural and micro structural properties of the obtained films have been investigated by means of high resolution X-ray diffraction, Raman spectroscopy and transmission microscopy observations on cross-sections techniques. We noted a close dependence of the crystallinity on the used substrate and the film thickness. By increasing the annealing temperature to 1000ºC and the film thickness to 100 nm, the electrical resistivity was decreased by several orders of magnitude. The film resistivity reaches approximately 3~4 x10-4 Ω.cm in a wide interval of temperature 77-320 K, making this material a promising candidate for a variety of applications.

Keywords: cobaltite, thin films, epitaxial growth, MOD, TEM

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Authors: Ayu Diar Sari, Sidharta Utama

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The main objective of this study is to examine the empirical association among strategic corporate social responsibility (Strategic CSR), corporate governance (CG), and firm performance by investigating their causal effects. In order to get the comprehensive result, this study uses CSR variables which consist of Strategic CSR, Non-Strategic CSR and CSR as a whole. Exerting the two stage least square (2SLS) method, the result showed that CG mechanism positively influences CSR, Non-Strategic CSR, and firm performance (both ROA and PBV). CSR and Non-Strategic CSR positively influence ROA. Meanwhile CSR, Strategic and Non-Strategic CSR positively influence PBV. Firm’s Strategic CSR engagement plays a significantly positive role in enhancing PBV. The results supported the social impact hypothesis, agency theory, and conflict resolution theory.

Keywords: corporate financial performance, corporate governance, corporate social responsibility, strategic corporate social responsibility

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Authors: Gabriel Roveda-Hoyos, Margarita Ramirez-Gomez, Adrian Perez, Diana Paola Serralde

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The objective of this study was to determine the variability of arbuscular mycorrhizal fungi (HFMA) communities associated with wild agraz plants (Vaccinium meridionale Swartz) in the Colombian Andes. This species is one of the most promising fruits within the genus Vaccinium because of the high content of anthocyanins and antioxidants in its fruits, and like other species of the Ericaceae family, it depends on the association with HFM for its development in the natural environment. In this study, the presence of mycorrhizae in wild communities of V. meridionale was evaluated, and their relationship with the edaphic and climatic conditions of the study area was analyzed. Sampling was conducted in the rural area of the municipalities of Raquira, and Chiquinquira, Chia, and Tabio in the departments of Cundinamarca and Boyaca, Colombia. Seven sites were selected, and in each site, 5 plants were randomly selected, root and soil samples were taken from each plant in the rhizosphere zone for the quantification of colonization and the presence of spores. The samples were collected on different soils, taxonomic orders Entisols, Inceptisols, and Alfisols, located at altitudes between 2,600 and 3,000 above sea level in the Eastern Cordillera of Colombia. The physicochemical characteristics of the soil were compared with the density of spores and the percentage of presence of mycorrhizae in the roots and variables with the morphometric and physiological characteristics of the plants. Four types of mutual associations were found: arbuscular mycorrhizae, ectendomycorrhiza, ericoid mycorrhizae, and endophytic septate fungi. The main results obtained show a predominance of spores of the genera Glomus and Acaulsopora, in most of the soils analyzed. The spore density of Glomeromycete fungi in the soil varied considerably between the different sites; it was higher ( > 50 spores/g of dry soil) in soil samples with lower bulk density and higher content of organic matter; in these soils a higher cation exchange capacity was found, as well as of nitrogen, calcium, magnesium, manganese and zinc concentration. It can be concluded that Vaccinium meridionale is able to establish in a natural way, association with HFMA.

Keywords: Ericaceae, Arbuscular mycorrhizae, Andes, soils, Glomus sp.

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Authors: Demelash Kassaye

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The Ethiopia case study reveals a unique model of community policing that has developed from a particular political context in which there is a history of violent political transition, a political structure characterized by ethnic federalism and a political ideology that straddles liberal capitalism and democracy on the one hand, and state-led development and centralized control on the other. The police see community policing as a way to reduce crime. Communities speak about community policing as an opportunity to take on policing responsibilities themselves. Both of these objectives are brought together in an overarching rhetoric of community policing as a way of ‘mobilizing for development’ – whereby the community cooperate with the police to reduce crime, which otherwise inhibits development progress. Community policing in Amhara has primarily involved the placement of Community Police Officers at the kebele level across the State. In addition, a number of structures have also been established in the community, including Advisory Councils, Conflict Resolving Committees, family police and the use of shoe shiner’s and other trade associations as police informants. In addition to these newly created structures, community policing also draws upon pre-existing customary actors, such as militia and elders. Conflict Resolving Committees, Community Police Officers and elders were reported as the most common first ports of call when community members experience a crime. The analysis highlights that the model of community policing in Amhara increased communities’ access to policing services, although this is not always attended by increased access to justice. Community members also indicate that public perceptions of the police have improved since the introduction of community policing, in part due to individual Community Police Officers who have, with limited resources, innovated some impressive strategies to improve safety in their neighborhoods. However, more broadly, community policing has provided the state with more effective surveillance of the population – a potentially oppressive function in the current political context. Ultimately, community policing in Amhara is anything but straightforward. It has been a process of attempting to demonstrate the benefits of newfound (and controversial) ‘democracy’ following years of dictatorship, drawing on generations of customary dispute resolution, providing both improved access to security for communities and an enhanced surveillance capacity for the state. For external actors looking to engage in community policing, this case study reveals the importance of close analysis in assessing potential merits, risks and entry points of programming. Factors found to be central in shaping the nature of community policing in the Amhara case include the structure of the political system, state-society relations, cultures dispute resolution and political ideology.

Keywords: community policing, community, militias, ethiopia

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Authors: N. Ould Cherchali, A. Tlemçani, M. S. Boucherit, A. Morsli

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Nature-inspired metaheuristic algorithms, particularly those founded on swarm intelligence, have attracted much attention over the past decade. Firefly algorithm has appeared in approximately seven years ago, its literature has enlarged considerably with different applications. It is inspired by the behavior of fireflies. The aim of this paper is the application of firefly algorithm for solving a nonlinear algebraic system. This resolution is needed to study the Selective Harmonic Eliminated Pulse Width Modulation strategy (SHEPWM) to eliminate the low order harmonics; results have been applied on multilevel inverters. The final results from simulations indicate the elimination of the low order harmonics as desired. Finally, experimental results are presented to confirm the simulation results and validate the efficaciousness of the proposed approach.

Keywords: firefly algorithm, metaheuristic algorithm, multilevel inverter, SHEPWM

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Authors: Raphael Palucci Rosa, Giuseppe Rosace

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Stereolithography (SLA) is one of the 3D-printing technologies that has been steadily growing in popularity for both industrial and personal applications due to its versatility, high accuracy, and low cost. Its printing process consists of using a light emitter to solidify photosensitive liquid resins layer-by-layer to produce solid objects. However, the majority of the resins used in SLA are derived from petroleum and characterized by toxicity, stability, and recalcitrance to degradation in natural environments. Aiming to develop an eco-friendly resin, in this work, different combinations of a standard commercial SLA resin (Peopoly UV professional) with a vegetable-based resin were investigated. To reach this goal, different mass concentrations (varying from 10 to 50 wt%) of acrylated epoxidized soybean oil (AESO), a vegetable resin produced from soyabean oil, were mixed with a commercial acrylate-based resin. 1.0 wt% of Diphenyl(2,4,6-trimethylbenzoyl) phosphine oxide (TPO) was used as photo-initiator, and the samples were printed using a Peopoly moai 130. The machine was set to operate at standard configurations when printing commercial resins. After the print was finished, the excess resin was drained off, and the samples were washed in isopropanol and water to remove any non-reacted resin. Finally, the samples were post-cured for 30 min in a UV chamber. FT-IR analysis was used to confirm the UV polymerization of the formulated resin with different AESO/Peopoly ratios. The signals from 1643.7 to 1616, which corresponds to the C=C stretching of the AESO acrylic acids and Peopoly acrylic groups, significantly decreases after the reaction. The signal decrease indicates the consumption of the double bonds during the radical polymerization. Furthermore, the slight change of the C-O-C signal from 1186.1 to 1159.9 decrease of the signals at 809.5 and 983.1, which corresponds to unsaturated double bonds, are both proofs of the successful polymerization. Mechanical analyses showed a decrease of 50.44% on tensile strength when adding 10 wt% of AESO, but it was still in the same range as other commercial resins. The elongation of break increased by 24% with 10 wt% of AESO and swelling analysis showed that samples with a higher concentration of AESO mixed absorbed less water than their counterparts. Furthermore, high-resolution prototypes were printed using both resins, and visual analysis did not show any significant difference between both products. In conclusion, the AESO resin was successful incorporated into a commercial resin without affecting its printability. The bio-based resin showed lower tensile strength than the Peopoly resin due to network loosening, but it was still in the range of other commercial resins. The hybrid resin also showed better flexibility and water resistance than Peopoly resin without affecting its resolution. Finally, the development of new types of SLA resins is essential to provide new sustainable alternatives to the commercial petroleum-based ones.

Keywords: 3D-printing, bio-based, resin, soybean, stereolithography

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Authors: Kwazikwenkosi Sikhakhane, Suvendi Rimer, Mpho Gololo, Khmaies Oahada, Adnan Abu-Mahfouz

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Medical ultrasound imaging is a crucial diagnostic technique due to its affordability and non-invasiveness compared to other imaging methods. However, the presence of speckle noise, which is a form of multiplicative noise, poses a significant obstacle to obtaining clear and accurate images in ultrasound imaging. Speckle noise reduces image quality by decreasing contrast, resolution, and signal-to-noise ratio (SNR). This makes it difficult for medical professionals to interpret ultrasound images accurately. To address this issue, various techniques have been developed to reduce speckle noise in ultrasound images, which improves image quality. This paper aims to review some of these techniques, highlighting the advantages and disadvantages of each algorithm and identifying the scenarios in which they work most effectively.

Keywords: image processing, noise, speckle, ultrasound

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Authors: Shahab Zomorodbakhsh, Hayron Nesa Motevasel

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Water soluble compoundes were attached to single-walled carbon nanotubes (SWNTs) to form water-soluble nano pigments. functionalized SWNTs were then characterized by Fourier Transform Infrared spectroscopy (FT-IR), Raman spectroscopy, UV analysis, Transmission electron microscopy (TEM)and defunctionalization test and Representative results concerning the solubility. The product can be dissolved in water and High-resolution transmission electron microscope images showed that the SWNTs were efficiently functionalized, thus the p-stacking interaction between aromatic rings and COOH of SWNTs was considered responsible for the high solubility and High transmission electron in singlewall nanotubes.

Keywords: functionalized CNTs, singlewalled carbon nanotubes, water soluble compoundes, nano pigments

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Authors: Kiran Nawaz, Ahmad Ali Shahid, Sehrish Iftikhar, Waheed Anwar, Muhammad Nasir Subhani

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Chili (Solanum annum L.) attacks by many fungal pathogens, including members of Oomycetes which are responsible for root rot in different chili growing areas of the world. Oomycetes pathogens cause economic losses in different regions of the Pakistan. Most of the plant tissues, including roots, crowns, fruit, and leaves, are vulnerable to Phytophthora capsici. It is very difficult to manage the Phytophthora root rot of chili as many commercial varieties are tremendously vulnerable to P. capsici. The causal agent of the disease was isolated on corn meal agar (CMA) and identified on a morphological basis by using available taxonomic keys. The pathogen was also confirmed on the molecular basis through internal transcribed spacer region and with other molecular markers.The Blastn results showed 100% homology with already reported sequences of P. capsici in NCBI database. Most of the farmers have conventionally relied on foliar fungicide applications to control Phytophthora root rot in spite of their incomplete effectiveness. In this study, in vitro plate assay, seed soaking and foliar applications of 6 fungicides were evaluated against root rot of chili. In vitro assay revealed that significant inhibition of linear growth was obtained with Triflumizole at 7.0%, followed by Thiophanate methyl (8.9%), Etridiazole (6.0%), Propamocarb (5.9%) and 7.5% with Mefenoxam and Iprodione for P. capsici. The promising treatments of in vitro plate bioassay were evaluated in pot experiments under controlled conditions in the greenhouse. All fungicides were applied after at 6-day intervals. Results of pot experiment showed that all treatments considerably inhibited the percentage of P. capsici root rot incidence. In addition, application of seed soaking with all six fungicides combined with the foliar spray of the same components showed the significant reduction in root rot incidence. The combine treatments of all fungicides as in vitro bioassay, seed soaking followed by foliar spray is considered non-harmful control methods which have advantages and limitation. Hence, these applications proved effective and harmless for the management of soil-borne plant pathogens.

Keywords: blastn, bioassay, corn meal agar(CMA), oomycetes

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Authors: Masood Hussain, Erol Pehlivan, Ahmet Avci, Ecem Guder

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Green synthesis of silver nanoparticles (AgNPs) was carried out by using echinacea flower extract as reducing/protecting agent. The effects of various operating parameters and additives on the dimensions such as stirring rate, temperature, pH of the solution, the amount of extract and concentration of silver nitrate were optimized in order to achieve monodispersed spherical and small size echinacea protected silver nanoparticles (echinacea-AgNPs) through biosynthetic method. The surface roughness and topography of synthesized metal nanoparticles were confirmed by using Atomic Force Microscopy (AFM). High-Resolution Transmission Electron Microscopic (HRTEM) results elaborated the formation of uniformly distributed Echinacea protected AgNPs (Echinacea-AgNPs) having an average size of 30.2±2nm.

Keywords: Echinacea flower extract, green synthesis, silver nanoparticles, morphology

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Authors: Grishma D. Solanki, Karshan Kandoriya

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In modern era of information age, digitalization has revolutionized like never before. Powerful computers, advanced photo editing software packages and high resolution capturing devices have made manipulation of digital images incredibly easy. As per as image forensics concerns, one of the most actively researched area are detection of copy move forgeries. Higher computational complexity is one of the major component of existing techniques to detect such tampering. Moreover, copy move forgery is usually performed in three steps. First, copying of a region in an image then pasting the same one in the same respective image and finally doing some post-processing like rotation, scaling, shift, noise, etc. Consequently, pseudo Zernike moment is used as a features extraction method for matching image blocks and as a primary factor on which performance of detection algorithms depends.

Keywords: copy-move image forgery, digital forensics, image forensics, image forgery

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Authors: Berhanu Keno Terfa

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Flash floods are among the most dangerous natural disasters that pose a significant threat to human existence. They occur frequently and can cause extensive damage to homes, infrastructure, and ecosystems while also claiming lives. Although flash floods can happen anywhere in the world, their impact is particularly severe in developing countries due to limited financial resources, inadequate drainage systems, substandard housing options, lack of early warning systems, and insufficient preparedness. To address these challenges, a comprehensive study has been undertaken to analyze and map flood inundation using Geographic Information System (GIS) techniques by considering various factors that contribute to flash flood resilience and developing effective mitigation strategies. Key factors considered in the analysis include slope, drainage density, elevation, Curve Number, rainfall patterns, land-use/cover classes, and soil data. These variables were computed using ArcGIS software platforms, and data from the Sentinel-2 satellite image (with a 10-meter resolution) were utilized for land-use/cover classification. Additionally, slope, elevation, and drainage density data were generated from the 12.5-meter resolution of the ALOS Palsar DEM, while other relevant data were obtained from the Ethiopian Meteorological Institute. By integrating and regularizing the collected data through GIS and employing the analytic hierarchy process (AHP) technique, the study successfully delineated flash flood hazard zones (FFHs) and generated a suitable land map for urban agriculture. The FFH model identified four levels of risk in Bishoftu City: very high (2106.4 ha), high (10464.4 ha), moderate (1444.44 ha), and low (0.52 ha), accounting for 15.02%, 74.7%, 10.1%, and 0.004% of the total area, respectively. The results underscore the vulnerability of many residential areas in Bishoftu City, particularly the central areas that have been previously developed. Accurate spatial representation of flood-prone areas and potential agricultural zones is crucial for designing effective flood mitigation and agricultural production plans. The findings of this study emphasize the importance of flood risk mapping in raising public awareness, demonstrating vulnerability, strengthening financial resilience, protecting the environment, and informing policy decisions. Given the susceptibility of Bishoftu City to flash floods, it is recommended that the municipality prioritize urban agriculture adaptation, proper settlement planning, and drainage network design.

Keywords: remote sensing, flush flood hazards, Bishoftu, GIS.

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Authors: Qiaosi Li, Frankie Kwan Kit Wong, Tung Fung

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Lightweight unmanned aerial vehicle (UAV) loading with novel sensors offers a low cost approach for data acquisition in complex environment. This study established a framework for applying UAV system in complex environment quick mapping and assessed the performance of UAV-based hyperspectral image and digital surface model (DSM) derived from photogrammetric point clouds for 13 species classification in wetland area Mai Po Inner Deep Bay Ramsar Site, Hong Kong. The study area was part of shallow bay with flat terrain and the major species including reedbed and four mangroves: Kandelia obovata, Aegiceras corniculatum, Acrostichum auerum and Acanthus ilicifolius. Other species involved in various graminaceous plants, tarbor, shrub and invasive species Mikania micrantha. In particular, invasive species climbed up to the mangrove canopy caused damage and morphology change which might increase species distinguishing difficulty. Hyperspectral images were acquired by Headwall Nano sensor with spectral range from 400nm to 1000nm and 0.06m spatial resolution image. A sequence of multi-view RGB images was captured with 0.02m spatial resolution and 75% overlap. Hyperspectral image was corrected for radiative and geometric distortion while high resolution RGB images were matched to generate maximum dense point clouds. Furtherly, a 5 cm grid digital surface model (DSM) was derived from dense point clouds. Multiple feature reduction methods were compared to identify the efficient method and to explore the significant spectral bands in distinguishing different species. Examined methods including stepwise discriminant analysis (DA), support vector machine (SVM) and minimum noise fraction (MNF) transformation. Subsequently, spectral subsets composed of the first 20 most importance bands extracted by SVM, DA and MNF, and multi-source subsets adding extra DSM to 20 spectrum bands were served as input in maximum likelihood classifier (MLC) and SVM classifier to compare the classification result. Classification results showed that feature reduction methods from best to worst are MNF transformation, DA and SVM. MNF transformation accuracy was even higher than all bands input result. Selected bands frequently laid along the green peak, red edge and near infrared. Additionally, DA found that chlorophyll absorption red band and yellow band were also important for species classification. In terms of 3D data, DSM enhanced the discriminant capacity among low plants, arbor and mangrove. Meanwhile, DSM largely reduced misclassification due to the shadow effect and morphological variation of inter-species. In respect to classifier, nonparametric SVM outperformed than MLC for high dimension and multi-source data in this study. SVM classifier tended to produce higher overall accuracy and reduce scattered patches although it costs more time than MLC. The best result was obtained by combining MNF components and DSM in SVM classifier. This study offered a precision species distribution survey solution for inaccessible wetland area with low cost of time and labour. In addition, findings relevant to the positive effect of DSM as well as spectral feature identification indicated that the utility of UAV-borne hyperspectral and photogrammetry deriving 3D data is promising in further research on wetland species such as bio-parameters modelling and biological invasion monitoring.

Keywords: digital surface model (DSM), feature reduction, hyperspectral, photogrammetric point cloud, species mapping, unmanned aerial vehicle (UAV)

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Authors: Sang Yeong Choi, Woo Sung Park

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This paper presents the architecture design of the robot operability assessment simulation testbed (called "ROAST") for the resolution of robot operability problems occurred during interactions between human operators and robots. The basic idea of the ROAST architecture design is to enable the easy composition of legacy or new simulation models according to its purpose. ROAST architecture is based on IEEE1516 High Level Architecture (HLA) of defense modeling and simulation. The ROAST architecture is expected to provide the foundation framework for the easy construction of a simulation testbed to order to assess the robot operability during the robotic system design. Some of ROAST implementations and its usefulness are demonstrated through a simple illustrative example.

Keywords: robotic system, modeling and simulation, simulation architecture, operability assessment

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Authors: Salam Khalifa, Naveed Ahmed

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We present a new method to reconstruct a temporally coherent 3D animation from single or multi-view RGB-D video data using unbiased feature point sampling. Given RGB-D video data, in form of a 3D point cloud sequence, our method first extracts feature points using both color and depth information. In the subsequent steps, these feature points are used to match two 3D point clouds in consecutive frames independent of their resolution. Our new motion vectors based dynamic alignment method then fully reconstruct a spatio-temporally coherent 3D animation. We perform extensive quantitative validation using novel error functions to analyze the results. We show that despite the limiting factors of temporal and spatial noise associated to RGB-D data, it is possible to extract temporal coherence to faithfully reconstruct a temporally coherent 3D animation from RGB-D video data.

Keywords: 3D video, 3D animation, RGB-D video, temporally coherent 3D animation

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Authors: Mohan Singh Mehata, R. K. Ratnesh

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CdSe, CdSe/ZnS, and CdSe/CdS core-shell quantum dots (QDs) of 3-4 nm were developed by using chemical route and following successive ion layer adsorption and reaction (SILAR) methods. The prepared QDs have been examined by using X-ray diffraction, high-resolution electron microscopy and optical spectroscopy. The photoluminescence (PL) quantum yield (QY) of core-shell QDs increases with respect to the core, indicating that the radiative rate increases by the formation of shell around core, as evident by the measurement of PL lifetime. Further, the PL of bovine serum albumin is quenched strongly by the presence of core-shall QDs and follow the Stern-Volmer (S-V) relation, whereas the lifetime does not follow the S-V relation, demonstrating that the observed quenching is predominantly static in nature. Among all the QDs, the CdSe/ZnS QDs shows the least cytotoxicity hence most biocompatibility.

Keywords: biocompatibility, core-shell quantum dots, photoluminescence and lifetime, sensing ability

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Authors: Z. Ghorannevis, E. Akbarnejad, B. Aghazadeh, M. Ghoranneviss

Abstract:

Carbon nanotubes (CNTs) modified with semiconductor nanocrystalline particles may find wide applications due to their unique properties. Here Cadmium Sulfide (CdS) nanoparticles were successfully grown on Multi-Walled Carbon Nanotubes (MWNTs) via a magnetron sputtering method for the first time. The CdS/MWNTs sample was characterized with X-ray diffraction (XRD), Field Emission Scanning and High Resolution Transmission Electron Microscopies (SEM/TEM) and four point probe. The obtained images show clearly the decoration of the MWNTs by the CdS nanoparticles, and the XRD measurements indicate the CdS structure as hexagonal type. Moreover, the physical properties of the CdS/MWNTs were compared with the physical properties of the CdS nanoparticles grown on the silicon. Electrical measurements of CdS and CdS/MWNTs reveal that CdS/MWNTs has lower resistivity than the CdS sample which may be due to the higher carrier concentrations.

Keywords: CdS, MWNTs, HRTEM, magnetron sputtering

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Authors: Zheng Wang, Zhenhong Li, Jon Mills

Abstract:

Ground-based synthetic aperture radar (GBSAR) represents a powerful remote sensing tool for deformation monitoring towards various geohazards, e.g. landslides, mudflows, avalanches, infrastructure failures, and the subsidence of residential areas. Unlike spaceborne SAR with a fixed revisit period, GBSAR data can be acquired with an adjustable temporal resolution through either continuous or discontinuous operation. However, challenges arise from processing high temporal-resolution continuous GBSAR data, including the extreme cost of computational random-access-memory (RAM), the delay of displacement maps, and the loss of temporal evolution. Moreover, repositioning errors between discontinuous campaigns impede the accurate measurement of surface displacements. Therefore, a versatile package with two complete chains is developed in this study in order to process both continuous and discontinuous GBSAR data and address the aforementioned issues. The first chain is based on a small-baseline subset concept and it processes continuous GBSAR images unit by unit. Images within a window form a basic unit. By taking this strategy, the RAM requirement is reduced to only one unit of images and the chain can theoretically process an infinite number of images. The evolution of surface displacements can be detected as it keeps temporarily-coherent pixels which are present only in some certain units but not in the whole observation period. The chain supports real-time processing of the continuous data and the delay of creating displacement maps can be shortened without waiting for the entire dataset. The other chain aims to measure deformation between discontinuous campaigns. Temporal averaging is carried out on a stack of images in a single campaign in order to improve the signal-to-noise ratio of discontinuous data and minimise the loss of coherence. The temporal-averaged images are then processed by a particular interferometry procedure integrated with advanced interferometric SAR algorithms such as robust coherence estimation, non-local filtering, and selection of partially-coherent pixels. Experiments are conducted using both synthetic and real-world GBSAR data. Displacement time series at the level of a few sub-millimetres are achieved in several applications (e.g. a coastal cliff, a sand dune, a bridge, and a residential area), indicating the feasibility of the developed GBSAR data processing package for deformation monitoring of a wide range of scientific and practical applications.

Keywords: ground-based synthetic aperture radar, interferometry, small baseline subset algorithm, deformation monitoring

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Authors: D. Hammad, D. P. Tonge

Abstract:

Rheumatoid arthritis (RA) is a disabling and common autoimmune disease during which the body's immune system attacks healthy tissues. This results in complicated and long-lasting actions being carried out by the immune system, which typically only occurs when the immune system encounters a foreign object. In the case of RA, the disease affects millions of people and causes joint inflammation, ultimately leading to the destruction of cartilage and bone. Interestingly, the disease mechanism still remains unclear. It is likely that RA occurs as a result of a complex interplay of genetic and environmental factors including an imbalance in the microorganism population inside our body. The human microbiome or microbiota is an extensive community of microorganisms in and on the bodies of animals, which comprises bacteria, fungi, viruses, and protozoa. Recently, the development of molecular techniques to characterize entire bacterial communities has renewed interest in the involvement of the microbiome in the development and progression of RA. We believe that an imbalance in some of the specific bacterial species in the gut, mouth and other sites may lead to atopobiosis; the translocation of these organisms into the blood, and that this may lead to changes in immune system status. The aim of this study was, therefore, to characterize the microbiome of RA serum samples in comparison to healthy control subjects using 16S rRNA gene amplification and sequencing. Serum samples were obtained from healthy control volunteers and from patients with RA both prior to, and following treatment. The bacterial community present in each sample was identified utilizing V4 region 16S rRNA amplification and sequencing. Bacterial identification, to the lowest taxonomic rank, was performed using a range of bioinformatics tools. Significantly, the proportions of the Lachnospiraceae, Ruminococcaceae, and Halmonadaceae families were significantly increased in the serum of RA patients compared with healthy control serum. Furthermore, the abundance of Bacteroides and Lachnospiraceae nk4a136_group, Lachnospiraceae_UGC-001, RuminococcaceaeUCG-014, Rumnococcus-1, and Shewanella was also raised in the serum of RA patients relative to healthy control serum. These data support the notion of a blood microbiome and reveal RA-associated changes that may have significant implications for biomarker development and may present much-needed opportunities for novel therapeutic development.

Keywords: blood microbiome, gut and oral bacteria, Rheumatoid arthritis, 16S rRNA gene sequencing

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Authors: Alpana Agarwal, Akhil Sharma

Abstract:

This work presents a fully differential CMOS amplifier consisting of two self-biased gain boosted inverter stages, that provides an alternative to the power hungry operational amplifier. The self-biasing avoids the use of external biasing circuitry, thus reduces the die area, design efforts, and power consumption. In the present work, regulated cascode technique has been employed for gain boosting. The Miller compensation is also applied to enhance the phase margin. The circuit has been designed and simulated in 1.8 V 0.18 µm CMOS technology. The simulation results show a high DC gain of 100.7 dB, Unity-Gain Bandwidth of 107.8 MHz, and Phase Margin of 66.7^o with a power dissipation of 286 μW and makes it suitable candidate for the high resolution pipelined ADCs.

Keywords: CMOS amplifier, gain boosting, inverter-based amplifier, self-biased inverter

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Authors: Hanbyul Kim, Hye-Jin Kin, Taehun Park, Woo Jun Sul, Susun An

Abstract:

Skin is the largest organ of the human body and can provide the diverse habitat for various microorganisms. The ecology of the skin surface selects distinctive sets of microorganisms and is influenced by both endogenous intrinsic factors and exogenous environmental factors. The diversity of the bacterial community in the skin also depends on multiple host factors: gender, age, health status, location. Among them, age-related changes in skin structure and function are attributable to combinations of endogenous intrinsic factors and exogenous environmental factors. Skin aging is characterized by a decrease in sweat, sebum and the immune functions thus resulting in significant alterations in skin surface physiology including pH, lipid composition, and sebum secretion. The present study gives a comprehensive clue on the variation of skin microbiota and the correlations between ages by analyzing and comparing the metagenome of skin microbiome using Next Generation Sequencing method. Skin bacterial diversity and composition were characterized and compared between two different age groups: younger (20 – 30y) and older (60 - 70y) Xian, Chinese women. A total of 73 healthy women meet two conditions: (I) living in Xian, China; (II) maintaining healthy skin status during the period of this study. Based on Ribosomal Database Project (RDP) database, skin samples of 73 participants were enclosed with ten most abundant genera: Chryseobacterium, Propionibacterium, Enhydrobacter, Staphylococcus and so on. Although these genera are the most predominant genus overall, each genus showed different proportion in each group. The most dominant genus, Chryseobacterium was more present relatively in Young group than in an old group. Similarly, Propionibacterium and Enhydrobacter occupied a higher proportion of skin bacterial composition of the young group. Staphylococcus, in contrast, inhabited more in the old group. The beta diversity that represents the ratio between regional and local species diversity showed significantly different between two age groups. Likewise, The Principal Coordinate Analysis (PCoA) values representing each phylogenetic distance in the two-dimensional framework using the OTU (Operational taxonomic unit) values of the samples also showed differences between the two groups. Thus, our data suggested that the composition and diversification of skin microbiomes in adult women were largely affected by chronological and physiological skin aging.

Keywords: next generation sequencing, age, Xian, skin microbiome

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Authors: Maxence Queyrel, Edi Prifti, Alexandre Templier, Jean-Daniel Zucker

Abstract:

Analysis of the human microbiome using metagenomic sequencing data has demonstrated high ability in discriminating various human diseases. Raw metagenomic sequencing data require multiple complex and computationally heavy bioinformatics steps prior to data analysis. Such data contain millions of short sequences read from the fragmented DNA sequences and stored as fastq files. Conventional processing pipelines consist in multiple steps including quality control, filtering, alignment of sequences against genomic catalogs (genes, species, taxonomic levels, functional pathways, etc.). These pipelines are complex to use, time consuming and rely on a large number of parameters that often provide variability and impact the estimation of the microbiome elements. Training Deep Neural Networks directly from raw sequencing data is a promising approach to bypass some of the challenges associated with mainstream bioinformatics pipelines. Most of these methods use the concept of word and sentence embeddings that create a meaningful and numerical representation of DNA sequences, while extracting features and reducing the dimensionality of the data. In this paper we present an end-to-end approach that classifies patients into disease groups directly from raw metagenomic reads: metagenome2vec. This approach is composed of four steps (i) generating a vocabulary of k-mers and learning their numerical embeddings; (ii) learning DNA sequence (read) embeddings; (iii) identifying the genome from which the sequence is most likely to come and (iv) training a multiple instance learning classifier which predicts the phenotype based on the vector representation of the raw data. An attention mechanism is applied in the network so that the model can be interpreted, assigning a weight to the influence of the prediction for each genome. Using two public real-life data-sets as well a simulated one, we demonstrated that this original approach reaches high performance, comparable with the state-of-the-art methods applied directly on processed data though mainstream bioinformatics workflows. These results are encouraging for this proof of concept work. We believe that with further dedication, the DNN models have the potential to surpass mainstream bioinformatics workflows in disease classification tasks.

Keywords: deep learning, disease prediction, end-to-end machine learning, metagenomics, multiple instance learning, precision medicine

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Authors: R Palson Kennedy, P.Kiran Sai

Abstract:

This article introduces machine learning (ML) researchers to the hurdles that geoscience problems present, as well as the opportunities for improvement in both ML and geosciences. This article presents a review from the data life cycle perspective to meet that need. Numerous facets of geosciences present unique difficulties for the study of intelligent systems. Geosciences data is notoriously difficult to analyze since it is frequently unpredictable, intermittent, sparse, multi-resolution, and multi-scale. The first half addresses data science’s essential concepts and theoretical underpinnings, while the second section contains key themes and sharing experiences from current publications focused on each stage of the data life cycle. Finally, themes such as open science, smart data, and team science are considered.

Keywords: Data science, intelligent system, machine learning, big data, data life cycle, recent development, geo science

Procedia PDF Downloads 129