Search results for: aerial photograph

Authors: Minjung Maing, Sibei Liu

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This research discusses the results of a study of window opening behavior of large housing developments in the high-density megacity of Hong Kong. The methods used for the study involved field observations using photo documentation of the four cardinal elevations (north, south-east, and west) of two large housing developments in a very dense urban area of approx. 46,000 persons per square meter within the city of Hong Kong. The targeted housing developments (A and B) are large public housing with a population of about 13,000 in each development of lower income. However, the mean income level in development A is about 40% higher than development B and home ownership is 60% in development A and 0% in development B. Mapping of the surrounding amenities and layout of the developments were also studied to understand the available activities to the residents. The photo documentation of the elevations was taken from November 2016 to February 2018 to gather a full spectrum of different seasons and both in the morning and afternoon (am/pm) times. From the photograph, the window opening behavior was measured by counting the amount of windows opened as a percentage of all the windows on that façade. For each date of survey data collected, weather data was recorded from weather stations located in the same region to collect temperature, humidity and wind speed. To further understand the behavior, simulation studies of microclimate conditions of the housing development was conducted using the software ENVI-met, a widely used simulation tool by researchers studying urban climate. Four major conclusions can be drawn from the data analysis and simulation results. Firstly, there is little change in the amount of window opening during the different seasons within a temperature range of 10 to 35 degrees Celsius. This means that people who tend to open their windows have consistent window opening behavior throughout the year and high tolerance of indoor thermal conditions. Secondly, for all four elevations the lower-income development B opened more windows (almost two times more units) than higher-income development A meaning window opening behavior had strong correlations with income level. Thirdly, there is a lack of correlation between outdoor horizontal wind speed and window opening behavior, as the changes of wind speed do not seem to affect the action of opening windows in most conditions. Similar to the low correlation between horizontal wind speed and window opening percentage, it is found that vertical wind speed also cannot explain the window opening behavior of occupants. Fourthly, there is a slightly higher average of window opening on the south elevation than the north elevation, which may be due to the south elevation being well shaded from high angle sun during the summer and allowing heat into units from lower angle sun during the winter season. These findings are important to providing insight into how to better design urban environments and indoor thermal environments for a liveable high density city.

Keywords: high-density housing, subtropical climate, urban behavior, window opening

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Authors: Jin Fan, M. Ala Saadeghvaziri

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Unmanned aerial vehicles (UAVs), also referred to as drones, equipped with various kinds of advanced detecting or surveying systems, are effective and low-cost in data acquisition, data delivery and sharing, which can benefit the building of infrastructures. This paper will give an overview of applications of drones in planning, designing, construction and maintenance of infrastructures. The drone platform, detecting and surveying systems, and post-data processing systems will be introduced, followed by cases with details of the applications. Challenges from different aspects will be addressed. Opportunities of drones in infrastructure include but not limited to the following. Firstly, UAVs equipped with high definition cameras or other detecting equipment are capable of inspecting the hard to reach infrastructure assets. Secondly, UAVs can be used as effective tools to survey and map the landscape to collect necessary information before infrastructure construction. Furthermore, an UAV or multi-UVAs are useful in construction management. UVAs can also be used in collecting roads and building information by taking high-resolution photos for future infrastructure planning. UAVs can be used to provide reliable and dynamic traffic information, which is potentially helpful in building smart cities. The main challenges are: limited flight time, the robustness of signal, post data analyze, multi-drone collaboration, weather condition, distractions to the traffic caused by drones. This paper aims to help owners, designers, engineers and architects to improve the building process of infrastructures for higher efficiency and better performance.

Keywords: bridge, construction, drones, infrastructure, information

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Authors: Reza Dehghani Bidgoli

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Information on different rangeland plants’ nutritive values at various phonological stages is important in rangelands management. This information helps rangeland managers to choose proper grazing times to achieve higher animal performance without detrimental effects on the rangeland vegetations. Effects of various plant parts’ phonological stages and vegetation types on reserve carbohydrates and forage quality indicators were investigated during the 2009 and 2010. Plant samples were collected in a completely randomized block (CRB) design. The species included, grasses (Secale montanum and Festuco ovina), forbs (Lotus corniculatus and Sanguisorba minor), and shrubs (Kochia prosterata and Salsola rigida). Aerial plant parts’ samples were oven-dried at 80oC for 24 hours, then analyzed for soluble carbohydrates, crude protein (CP), acid detergent fiber (ADF), dry matter digestible (DMD), and metabolizable energy (ME). Results showed that plants at the seedling stage had more reserve carbohydrates and from the three vegetation types (grass, forbs, and shrub), forbs contained more soluble carbohydrates compared to the other two (grasses and shrubs). Differences in soluble carbohydrate contents of different species at various phonological stages in 2 years were statistically significant. The forage quality indicators (CP, ADF, DMD, and ME) in different species, in different vegetation types, in the 2 years were statistically significant, except for the CP.

Keywords: grazing, soluble carbohydrate, protein, fiber, metabolizeable energy

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Authors: Karima Sekkoum Abdelkrim Cheriti, Leila Feguigui

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Algeria has a large plant biodiversity accounting more than 4125 species (123 Families) and is endowed with resources of medicinal plants growing on various bioclimatic zones from subhumide to semi-arid and Saharan. On the other hand, the ethnopharmacology investigation remains the principal way to improve, evaluate, and finding bioactive substances derived from medicinal plants. In continuation of our works in Saharan ethpharmacopeae and phytochemistry of Saharan medicinal plants, we focus our attention on the importance of local ethnopharmacology especially to treat gastro-intestinal disorders in the south west of Algeria (El Baydh, Naama and Bechar region) as platform for bioactive substances discovery and further development. Our present investigation deals with an ethnopharmacological study on medicinal plants used for the treatment of gastro-intestinal disorders in the south west of Algeria. The study presents the uses of plants in local traditional herbal medicines, determines the homogeneity of informant traditional knowledge and the preferred medicinal plants used to treat gastro-intestinal disorders. The results indicated that Asteraceae and Lamiaceae are the most locally used families and medicines were prepared in the form of powder or infusion and used orally. Aerial parts were the most frequently used plant part. Thus, the results can be used as platform for bioactive substances discovery and further development especially for the preferred plant species used in the treatment of gastro-intestinal disorders.

Keywords: ethnopharmacology, gastro-intestinal, phytochemical, South Algeria, Sahara, endemic species

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Authors: Johnson Okoduwa Imumbhon, Mohammad Didarul Alam, Yiding Cao

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Structural analyses are commonly employed to test the integrity of aircraft component systems in the design stage to demonstrate the capability of the structural components to withstand what it was designed for, as well as to predict potential failure of the components. The analyses are also essential for weight minimization and selecting the most resilient materials that will provide optimal outcomes. This research focuses on testing the structural nature of a high-lift low Reynolds number airfoil profile design, the Selig S1223, under certain loading conditions for a drone model application. The wing (ribs, spars, and skin) of the drone model was made of carbon fiber-reinforced polymer and designed in SolidWorks, while the finite element analysis was carried out in ANSYS mechanical in conjunction with the lift and drag forces that were derived from the aerodynamic airfoil analysis. Additionally, modal analysis was performed to calculate the natural frequencies and the mode shapes of the wing structure. The structural strain and stress determined the minimal deformations under the wing loading conditions, and the modal analysis showed the prominent modes that were excited by the given forces. The research findings from the structural analysis of the S1223 high-lift airfoil indicated that it is applicable for use in an unmanned aerial vehicle as well as a novel reciprocating-airfoil-driven vertical take-off and landing (VTOL) drone model.

Keywords: CFRP, finite element analysis, high-lift, S1223, strain, stress, VTOL

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Authors: Muhammad Umair Mushtaq, Ameena Iqbal, Muhammad Aqib Hassan Ali Khan, Ismat Nawaz, Sohail Yousaf, Mazhar Iqbal

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Heavy metals are one of the priority pollutants as they pose serious health and environmental threats. They can be removed by various physiochemical methods but are costly and responsible for additional environmental problems. Bioremediation that exploits plants and their associated microbes have been referred as cost effective and environmental friendly technique. In this study, a pot experiment was conducted in a greenhouse to evaluate the potential of Celosia cristata and effects of bacteria, Pseudomonas japonica, and organic amendment moss/compost on tolerating/accumulating heavy metals. Two weeks old seedlings were transferred to soil in pots, and after four weeks they were inoculated with bacterial strain, while after growth of six weeks they were watered with a metal containing synthetic wastewater and were harvested after a growth period of nine weeks. After harvesting, morphological and physiological parameters and metal content of plants were measured. The results showed highest plant growth and biomass production in case of organic amendments while highest metal uptake has been found in non-amended pots. Positive controls have shown highest Pb uptake of 2900 mg/kg DW, while P. japonica amended pots have shown highest Cd, Cr, Ni and Cu uptake of 963.53, 1481.17, 1022.01 and 602.17 mg/kg DW, respectively. In conclusion organic amendments have strong impacts on growth enhancement while P. japonica enhances metal translocation and accumulation to aerial parts with little significant involvement in plant growth.

Keywords: ornamental plants, plant microbe interaction, amendments, bacteria

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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: Catalina Albornoz, Giacomo Barbieri

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Crop monitoring has shown to reduce vulnerability to spreading plagues and pathologies in crops. Remote sensing with Unmanned Aerial Vehicles (UAVs) has made crop monitoring more precise, cost-efficient and accessible. Nowadays, remote monitoring involves calculating maps of vegetation indices by using different software that takes either Truecolor (RGB) or multispectral images as an input. These maps are then used to segment the crop into management zones. Finally, knowing the spectral signature of a crop (the reflected radiation as a function of wavelength) can be used as an input for decision-making and crop characterization. The calculation of vegetation indices using software such as Pix4D has high precision for monoculture plantations. However, this paper shows that using this software on mixed crops may lead to errors resulting in an incorrect segmentation of the field. Within this work, authors propose to filter all the elements different from the main crop before the calculation of vegetation indices and the spectral signature. A filter based on the Sobel method for border detection is used for filtering a coffee crop. Results show that segmentation into management zones changes with respect to the traditional situation in which a filter is not applied. In particular, it is shown how the values of the spectral signature change in up to 17% per spectral band. Future work will quantify the benefits of filtering through the comparison between in situ measurements and the calculated vegetation indices obtained through remote sensing.

Keywords: coffee, filtering, mixed crop, precision agriculture, remote sensing, spectral signature

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Authors: Mouffok Ahlem, Belhamra Mohamed, Mouffok Sihem

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The use of nitrogen fertilizers inevitable consequence, the increase in the nitrate content of water, which may contribute to the production of nitrite and the formation of carcinogenic nitrosamines. The nitrogen fertilizer may also affect the structure and function of the microbial community. And the fight against eutrophication of aquatic environments represents a cost to the student statements. The agronomic, ecological and economic legumes such as faba beans and alfalfa are not demonstrated, especially in the case of semi-arid and arid areas. Osmotic stress due to drought and / or salinity deficit, nutritional deficiencies is the major factors limiting symbiotic nitrogen fixation and productivity of pulses. To study the symbiotic nitrogen fixation in faba bean (Vicia faba L.) and alfalfa (Medicago sativa L.) in the region of Biskra, we used soil samples collected from 30 locations. This work has identified several issues of ecological and agronomic interest. Evaluation of symbiotic potential of soils in the region of Biskra; by trapping technique, show different levels of susceptibility to rhizobial microflora. The effectiveness of the rhizobial symbiosis in both legumes indicates that air dry biomass and the amount of nitrogen accumulated in the aerial part, depends mainly on the rate of nodulation and regardless of the species and locality. The correlation between symbiotic nitrogen fixation and some physico-chemical properties of soils shows that symbiotic nitrogen fixation in both legumes is strongly related to soil conditions of the soil. Salinity disrupts the physiological process of growth, development and more particularly that of the symbiotic fixation of atmospheric nitrogen. Against by phosphorus promotes rhizobial symbiosis.

Keywords: rhizobia, faba bean, alfalfa, salinity

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Authors: Esma Hande Alıcı, Gülnur Arabacı

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Antioxidants are compounds or systems that can safely interact with free radicals and terminate the chain reaction before vital molecules are damaged. The anti-oxidative effectiveness of these compounds depends on their chemical characteristics and physical location within a food (proximity to membrane phospholipids, emulsion interfaces, or in the aqueous phase). Antioxidants (e.g., flavonoids, phenolic acids, tannins, vitamin C, vitamin E) have diverse biological properties, such as antiinflammatory, anti-carcinogenic and anti-atherosclerotic effects, reduce the incidence of coronary diseases and contribute to the maintenance of gut health by the modulation of the gut microbial balance. Plants are excellent sources of antioxidants especially with their high content of phenolic compounds. Raphanus raphanistrum L., the wild radish, is a flowering plant in the family Brassicaceae. It grows in Asia and Mediterranean region. It has been introduced into most parts of the world. It spreads rapidly, and is often found growing on roadsides or in other places where the ground has been disturbed. It is an edible plant, in Turkey its fresh aerial parts are mostly consumed as a salad with olive oil and lemon juice after boiled. The leaves of the plant are also used as anti-rheumatic in traditional medicine. In this study, we determined the antioxidant capacity of two different solvent fractions (methanol and ethyl acetate) obtained from Raphanus raphanistrum L. plant leaves. Antioxidant capacity of the plant was introduced by using three different methods: DPPH radical scavenging activity, CUPRAC (Cupric Ion Reducing Antioxidant Capacity) activity and Reducing power activity.

Keywords: antioxidant activity, antioxidant capacity, Raphanis raphanistrum L., wild radish

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Authors: Rabie Fadil, Parshuram Aarotale, Shubha Majumder, Bijay Guargain

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Hemorrhage is the loss of blood from the circulatory system and leading cause of battlefield and postpartum related deaths. Early detection of hemorrhage remains the most effective strategy to reduce mortality rate caused by traumatic injuries. In this study, we investigated the physiological changes via non-invasive cardiac signals at rest and under different hemorrhage conditions simulated through graded lower-body negative pressure (LBNP). Simultaneous electrocardiogram (ECG), photoplethysmogram (PPG), blood pressure (BP), impedance cardiogram (ICG), and phonocardiogram (PCG) were acquired from 10 participants (age:28 ± 6 year, weight:73 ± 11 kg, height:172 ± 8 cm). The LBNP protocol consisted of applying -20, -30, -40, -50, and -60 mmHg pressure to the lower half of the body. Beat-to-beat heart rate (HR), systolic blood pressure (SBP), diastolic blood pressure (DBP), and mean aerial pressure (MAP) were extracted from ECG and blood pressure. Systolic amplitude (SA), systolic time (ST), diastolic time (DT), and left ventricle Ejection time (LVET) were extracted from PPG during each stage. Preliminary results showed that the application of -40 mmHg i.e. moderate stage simulated hemorrhage resulted significant changes in HR (85±4 bpm vs 68 ± 5bpm, p < 0.01), ST (191 ± 10 ms vs 253 ± 31 ms, p < 0.05), LVET (350 ± 14 ms vs 479 ± 47 ms, p < 0.05) and DT (551 ± 22 ms vs 683 ± 59 ms, p < 0.05) compared to rest, while no change was observed in SA (p > 0.05) as a consequence of LBNP application. These findings demonstrated the potential of cardiac signals in detecting moderate hemorrhage. In future, we will analyze all the LBNP stages and investigate the feasibility of other physiological signals to develop a predictive machine learning model for early detection of hemorrhage.

Keywords: blood pressure, hemorrhage, lower-body negative pressure, LBNP, machine learning

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Authors: Yildiray Korkmaz, Mehmet Aksoy

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In today's operations, countries want to reach their aims in the shortest way due to economical, political and humanitarian aspects. The most effective way of achieving this goal is to be able to penetrate strategic targets. Strategic targets are generally located deep inside of the countries and are defended by modern and efficient surface to air missiles (SAM) platforms which are operated as integrated with Intelligence, Surveillance and Reconnaissance (ISR) systems. On the other hand, these high valued targets are buried deep underground and hardened with strong materials against attacks. Therefore, to penetrate these targets requires very detailed intelligence. This intelligence process should include a wide range that is from weaponry to threat assessment. Accordingly, the framework of the attack package will be determined. This mission package has to execute missions in a high threat environment. The way to minimize the risk which depends on loss of life is to use packages which are formed by UAVs. However, some limitations arising from the characteristics of UAVs restricts the performance of the mission package consisted of UAVs. So, the mission package should be formed with UAVs under the leadership of a fifth generation manned aircraft. Thus, we can minimize the limitations, easily penetrate in the deep inside of the enemy territory with minimum risk, make a decision according to ever-changing conditions and finally destroy the strategic targets. In this article, the strengthens and weakness aspects of UAVs are examined by SWOT analysis. And also, it revealed features of a mission package and presented as an example what kind of a mission package we should form in order to get marginal benefit and penetrate into strategic targets with the development of autonomous mission execution capability in the near future.

Keywords: UAV, autonomy, mission package, strategic attack, mission planning

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Authors: Ankit Sharma, Mudit Sachan, Anurag Prakash

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Rapid growth in data acquisition technologies through drones, have led to advances and interests in collecting high-resolution images of geological fields. Being advantageous in capturing high volume of data in short flights, a number of challenges have to overcome for efficient analysis of this data, especially while data acquisition, image interpretation and processing. We introduce a method that allows effective mapping of geological fields using photogrammetric data of surfaces, drainage area, water bodies etc, which will be captured by airborne vehicles like UAVs, we are not taking satellite images because of problems in adequate resolution, time when it is captured may be 1 yr back, availability problem, difficult to capture exact image, then night vision etc. This method includes advanced automated image interpretation technology and human data interaction to model structures and. First Geological structures will be detected from the primary photographic dataset and the equivalent three dimensional structures would then be identified by digital elevation model. We can calculate dip and its direction by using the above information. The structural map will be generated by adopting a specified methodology starting from choosing the appropriate camera, camera’s mounting system, UAVs design ( based on the area and application), Challenge in air borne systems like Errors in image orientation, payload problem, mosaicing and geo referencing and registering of different images to applying DEM. The paper shows the potential of using our method for accurate and efficient modeling of geological structures, capture particularly from remote, of inaccessible and hazardous sites.

Keywords: digital elevation model, mapping, photogrammetric data analysis, geological structures

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Authors: Petra Hypšová, Martin Seitl

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One of the challenges of forensic psychology is to detect deception during a face-to-face interview. In addition to the classical approaches of monitoring the utterance and its components, detection is also sought by observing behavioral and physiological changes that occur as a result of the increased emotional and cognitive load caused by the production of distorted information. Typical are changes in facial temperature, eye movements and their fixation, pupil dilation, emotional micro-expression, heart rate and its variability. Expanding technological capabilities have opened the space to detect these psychophysiological changes and behavioral manifestations through non-contact technologies that do not interfere with face-to-face interaction. Non-contact deception detection methodology is still in development, and there is a lack of studies that combine multiple non-contact technologies to investigate their accuracy, as well as studies that show how different types of lies produced by different interviewers affect physiological and behavioral changes. The main objective of this study is to apply a specific non-contact technology for deception detection. The next objective is to investigate scenarios in which non-contact deception detection is possible. A series of psychophysiological experiments using infrared thermal imaging, eye tracking and behavioral analysis with FaceReader 9.0 software was used to achieve our goals. In the laboratory experiment, 16 adults (12 women, 4 men) between 18 and 35 years of age (SD = 4.42) were instructed to produce alternating prepared and spontaneous truths and lies. The baseline of each proband was also measured, and its results were compared to the experimental conditions. Because the personality of the examiner (particularly gender and facial appearance) to whom the subject is lying can influence physiological and behavioral changes, the experiment included four different interviewers. The interviewer was represented by a photograph of a face that met the required parameters in terms of gender and facial appearance (i.e., interviewer likability/antipathy) to follow standardized procedures. The subject provided all information to the simulated interviewer. During follow-up analyzes, facial temperature (main ROIs: forehead, cheeks, the tip of the nose, chin, and corners of the eyes), heart rate, emotional expression, intensity and fixation of eye movements and pupil dilation were observed. The results showed that the variables studied varied with respect to the production of prepared truths and lies versus the production of spontaneous truths and lies, as well as the variability of the simulated interviewer. The results also supported the assumption of variability in physiological and behavioural values during the subject's resting state, the so-called baseline, and the production of prepared and spontaneous truths and lies. A series of psychophysiological experiments provided evidence of variability in the areas of interest in the production of truths and lies to different interviewers. The combination of technologies used also led to a comprehensive assessment of the physiological and behavioral changes associated with false and true statements. The study presented here opens the space for further research in the field of lie detection with non-contact technologies.

Keywords: emotional expression decoding, eye-tracking, functional infrared thermal imaging, non-contact deception detection, psychophysiological experiment

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Authors: V. Santamarina Campos, M. de Miguel Molina, B. de Miguel Molina, M. Á. Carabal Montagud

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With this contribution, we want to show a successful example of the application of the Design Thinking methodology, in the European project 'Technology transfer of Remotely Piloted Aircraft Systems (RPAS) for the creative industry'. The use of this methodology has allowed us to design and build a drone, based on the real needs of prospective users. It has demonstrated that this is a powerful tool for generating innovative ideas in the field of robotics, by focusing its effectiveness on understanding and solving real user needs. In this way, with the support of an interdisciplinary team, comprised of creatives, engineers and economists, together with the collaboration of prospective users from three European countries, a non-linear work dynamic has been created. This teamwork has generated a sense of appreciation towards the creative industries, through continuously adaptive, inventive, and playful collaboration and communication, which has facilitated the development of prototypes. These have been designed to enable filming and photography in interior spaces, within 13 sectors of European creative industries: Advertising, Architecture, Fashion, Film, Antiques and Museums, Music, Photography, Televison, Performing Arts, Publishing, Arts and Crafts, Design and Software. Furthermore, it has married the real needs of the creative industries, with what is technologically and commercially viable. As a result, a product of great value has been obtained, which offers new business opportunities for small companies across this sector.

Keywords: design thinking, design for effectiveness, methodology, active toolkit, storyboards, PAR, focus group, innovation, RPAS, indoor drone, aerial film, creative industry, end users, stakeholder

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Authors: Bo Wang

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The geometric processing of multi-source remote sensing data using control data of different scale and different accuracy is an important research direction of multi-platform system for earth observation. In the existing block bundle adjustment methods, as the controlling information in the adjustment system, the approach using single observation scale and precision is unable to screen out the control information and to give reasonable and effective corresponding weights, which reduces the convergence and adjustment reliability of the results. Referring to the relevant theory and technology of quotient space, in this project, several subjects are researched. Multi-layer quotient space of multi-geometric features is constructed to describe and filter control data. Normalized granularity merging mechanism of multi-layer control information is studied and based on the normalized scale factor, the strategy to optimize the weight selection of control data which is less relevant to the adjustment system can be realized. At the same time, geometric positioning experiment is conducted using multi-source remote sensing data, aerial images, and multiclass control data to verify the theoretical research results. This research is expected to break through the cliché of the single scale and single accuracy control data in the adjustment process and expand the theory and technology of photogrammetry. Thus the problem to process multi-source remote sensing data will be solved both theoretically and practically.

Keywords: multi-source image geometric process, high precision geometric positioning, quotient space of multi-geometric features, optimized weight selection

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Authors: Nassim Belkacem, Amina Azzam, Dalila Haouchine, Kahina Bennacer, Samira Soufit

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Objective: To evaluate the antioxidant activity of the methanolic extract along with the antimicrobial activity of the essential oil of the aerial parts of Rosmarinus officinalis L. collected in the region of Bejaia (northern center of Algeria). Materials and methods: The polyphenols and flavonoids contents of the methanolic extract were measured. The antioxidant activity was evaluated using two methods: the ABTS method and DPPH assay. The antimicrobial activity was studied by the agar diffusion method against five bacterial strains (Three Gram positive strains and two Gram negative strains) and one fungus. Results: The total polyphenol and flavonoid content was about 43.8 mg gallic acid equivalent per gram (GA Eq/g) and 7.04 mg quercetin equivalent per gram (Q Eq/g), respectively. In the ABTS assay, the rosemary extract has shown an inhibition of 98.02% at the concentration of 500ug/ml with a half maximal inhibitory concentration value (IC50) of 194.92ug/ml. The results of DPPH assay have shown that the rosemary extract has an inhibition of 94.67 % with an IC50 value of 17.87ug/ml, which is lower than that of Butylhydroxyanisol (BHA) about 6.03ug/ml and ascorbic acid about 1.24μg/ml. The yield in essential oil of rosemary obtained by hydrodistillation was 1.42%. Based on the determination of the diameter of inhibition, different antimicrobial activity of the essential oil was revealed against the six tested microbes. Escherichia coli from the University Hospital (UH), Streptococcus aureus (UH) and Pseudomonas aeruginosa ATCC have a minimum inhibitory concentration value (MIC) of 62.5µl/ml. However, Bacillus sp (UH) and Staphylococcus aureus ATCC have an MIC value of 125μl/ml. The inhibition zone against Candida sp was about 24 mm. The aromatograms showed that the essential oil of rosemary exercises an antifungal activity more important than the antibacterial one.

Keywords: Rosmarinus officinalis L., maceration, essential oil, antioxidant, antimicrobial activity

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Authors: Megan Lindsey

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Background: Globalization presents international social work with both opportunities and challenges. Thus, the design of this international experience aligns with the three charges of the Commission on Global Social Work Education. An international collaborative effort between an American and Scottish University Social Work Program was based on an established University agreement. The presentation provides an overview of an international study abroad among American and Scottish Social Work students. Further, presenters will discuss the opportunities of international collaboration and the challenges of the project. First, we will discuss the process of a successful international collaboration. This discussion will include the planning, collaboration, execution of the experience, along with its application to the international field of social work. Second, we will discuss the development and implementation of participatory action research in which the student engage to enhance their learning experience. A collaborative qualitative research project was undertaken with three goals. First, students gained experience in Scottish social services, including agency visits and presentations. Second, a collaboration between American and Scottish MSW Students allowed the exchange of ideas and knowledge about services and social work education. Third, students collaborated on a qualitative research method to reflect on their social work education and the formation of their professional identity. Methods/Methodology: American and Scottish students engaged in participatory action research by using Photovoice methods while studying together in Scotland. The collaboration between faculty researchers framed a series of research questions. Both universities obtained IRB approval and trained students in Photovoice methods. The student teams used the research question and Photovoice method to discover images that represented their professional identity formation. Two Photovoice goals grounded the study's research question. First, the methods enabled the individual students to record and reflect on their professional strengths and concerns. Second, student teams promoted critical dialogue and knowledge about personal and professional issues through large and small group discussions of photographs. Results: The international participatory approach generated the ability for students to contextualize their common social work education and practice experiences. Team discussions between representatives of each country resulted in understanding professional identity formation and the processes of social work education that contribute to that identity. Students presented the photograph narration of their knowledge and understanding of international social work education and practice. Researchers then collaborated on finding common themes. The results found commonalities in the quality and depth of social work education. The themes found differences regarding how professional identity is formed. Students found great differences between their and American accreditation and certification. Conclusions: Faculty researchers’ collaboration themes sought to categorize the students’ experiences of their professional identity. While the social work education systems are similar, there are vast differences. The Scottish themes noted structures within American social work not found in the United Kingdom. The American researchers noted that Scotland, as does the United Kingdom, relies on programs, agencies, and the individual social worker to provide structure to identity formation. Other themes will be presented.

Keywords: higher education curriculum, international collaboration, social sciences, action research

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Authors: Luiz G. Véras, Felipe L. Medeiros, Lamartine F. Guimarães

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This work approaches the automatic planning of paths for Unmanned Aerial Vehicles (UAVs) through the application of the Rapidly Exploring Random Tree Star-Smart (RRT*-Smart) algorithm. RRT*-Smart is a sampling process of positions of a navigation environment through a tree-type graph. The algorithm consists of randomly expanding a tree from an initial position (root node) until one of its branches reaches the final position of the path to be planned. The algorithm ensures the planning of the shortest path, considering the number of iterations tending to infinity. When a new node is inserted into the tree, each neighbor node of the new node is connected to it, if and only if the extension of the path between the root node and that neighbor node, with this new connection, is less than the current extension of the path between those two nodes. RRT*-smart uses an intelligent sampling strategy to plan less extensive routes by spending a smaller number of iterations. This strategy is based on the creation of samples/nodes near to the convex vertices of the navigation environment obstacles. The planned paths are smoothed through the application of the method called quintic pythagorean hodograph curves. The smoothing process converts a route into a dynamically-viable one based on the kinematic constraints of the vehicle. This smoothing method models the hodograph components of a curve with polynomials that obey the Pythagorean Theorem. Its advantage is that the obtained structure allows computation of the curve length in an exact way, without the need for quadratural techniques for the resolution of integrals.

Keywords: path planning, path smoothing, Pythagorean hodograph curve, RRT*-Smart

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Authors: Ya-Li Tsai

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Nitrogen is a vital element crucial for crop growth, significantly influencing crop yield. In rice cultivation, farmers often apply substantial nitrogen fertilizer to maximize yields. However, excessive nitrogen application increases the risk of lodging and pest infestation, leading to yield losses. Additionally, conventional flooded irrigation methods consume significant water resources, necessitating precise agricultural and intelligent water management systems. In this study, it leveraged physiological data and field images captured by unmanned aerial vehicles, considering fertilizer treatment and irrigation as key factors. Statistical models incorporating rice physiological data, yield, and vegetation indices from image data were developed. Missing physiological data were addressed using multiple imputation and regression methods, and regression models were established using principal component analysis and stepwise regression. Target nitrogen accumulation at key growth stages was identified to optimize fertilizer application, with the difference between actual and target nitrogen accumulation guiding recommendations for ear dressing dosage. Field experiments conducted in 2022 validated the recommended ear dressing dosage, demonstrating no significant difference in final yield compared to traditional fertilizer levels under alternate wetting and drying irrigation. These findings highlight the efficacy of applying recommended dosages based on fertilizer decision models, offering the potential for reduced fertilizer use while maintaining yield in rice cultivation.

Keywords: intelligent fertilizer management, nitrogen top and ear dressing fertilizer, rice, yield optimization

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Authors: Ozlem Bahadir Acikara, Mert Ilhan, Ekin Kurtul, Karel Smejkal, Esra Kupeli Akkol

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Present study is aimed to investigate in vitro inhibitory effects of the extracts prepared from the aerial parts of Podospermum canum (Asteraceae) on hyaluronidase, collagenase, and elastase enzymes using a bioassay-guided fractionation. Inhibitory effects of the extract, sub-extracts, fractions obtained by column chromatography, and isolated compounds on collagenase, elastase, and hyaluronidase were performed by using in vitro enzyme inhibitory assays based on spectrophotometric evaluation. The ethyl acetate and remaining water extracts prepared from the plant displayed significant inhibitory activities on collagenase and elastase, while petroleum ether and chloroform extracts did not show any inhibitory activity. Eleven known compounds: arbutin, 6'-O-caffeoylarbutin, cichoriin, 3,5-dicaffeoylquinic acid methyl ester, apigenin-7-O-β-glucoside, luteolin-7-O-β-glucoside, apigenin-7-O-β-rutinoside, isoorientin, orientin, vitexin, procatechuic acid, and compound 4-hydroxy-benzoic acid 4-(6-O-α-rhamnopyranosyl-β-glucopyranosyl) benzyl ester have been obtained from ethyl acetate sub-extract of the plant through bioassay-guided fractionation and isolation. Results of the present study have revealed that among the isolated compounds, apigenin-7-O-β-glucoside, luteolin-7-O-β-glucoside, apigenin-7-O-β-rutinoside and isoorientin showed potent enzyme inhibitory activities. However, methanolic extract of P. canum displayed a greater inhibitory activity than fractions and isolated compounds both on collagenase and elastase.

Keywords: Asteraceae, collagenase, elastase, hyaluronidase, Podospermum canum

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Authors: Ronald Collins, Jonathon Coleman, Joel Dasari, George Holt, Carl Metelko, Matthew Murdoch, Alexander Morgan, Yan-Jie Schnellbach, Robert Mills, Gareth Edwards, Alexander Roberts

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At the Wylfa Magnox Power Plant between 2014–2016, the VIDARR prototype anti-neutrino detector was deployed. It is comprised of extruded plastic scintillating bars measuring 4 cm × 1 cm × 152 cm and utilised wavelength shifting fibres (WLS) and multi-pixel photon counters (MPPCs) to detect and quantify radiation. During deployment, it took cosmic muon data in accidental coincidence with the anti-neutrino measurements with the power plant site buildings obscuring the muon sky. Cosmic muons have a significantly higher probability of being attenuated and/or absorbed by denser objects, and so one-sided cosmic muon tomography was utilised to image the reactor site buildings. In order to achieve clear building outlines, a control data set was taken at the University of Liverpool from 2016 – 2018, which had minimal occlusion of the cosmic muon flux by dense objects. By taking the ratio of these two data sets and using GEANT4 simulations, it is possible to perform a one-sided cosmic muon tomography analysis. This analysis can be used to discern specific buildings, building heights, and features at the Wylfa reactor site, including the reactor core/reactor core shielding using ∼ 3 hours worth of cosmic-ray detector live time. This result demonstrates the feasibility of using cosmic muon analysis to determine a segmented detector’s location with respect to surrounding buildings, assisted by aerial photography or satellite imagery.

Keywords: anti-neutrino, GEANT4, muon, tomography, occlusion

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Authors: Nur Nadhirah Rusyda Rosnan, Nursuhaili Najwa Masrol, Nurul Fatiha MD Nor, Mohammad Zafrullah Mohammad Salim, Sim Choon Cheak

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Accurate inventories of oil palm planted areas are crucial for plantation management as this would impact the overall economy and production of oil. One of the technological advancements in the oil palm industry is semi-automated palm counting, which is replacing conventional manual palm counting via digitizing aerial imagery. Most of the semi-automated palm counting method that has been developed was limited to mature palms due to their ideal canopy size represented by satellite image. Therefore, immature palms were often left out since the size of the canopy is barely visible from satellite images. In this paper, an approach using a morphological filter and high-resolution satellite image is proposed to detect immature palm trees. This approach makes it possible to count the number of immature oil palm trees. The method begins with an erosion filter with an appropriate window size of 3m onto the high-resolution satellite image. The eroded image was further segmented using watershed segmentation to delineate immature palm tree regions. Then, local minimum detection was used because it is hypothesized that immature oil palm trees are located at the local minimum within an oil palm field setting in a grayscale image. The detection points generated from the local minimum are displaced to the center of the immature oil palm region and thinned. Only one detection point is left that represents a tree. The performance of the proposed method was evaluated on three subsets with slopes ranging from 0 to 20° and different planting designs, i.e., straight and terrace. The proposed method was able to achieve up to more than 90% accuracy when compared with the ground truth, with an overall F-measure score of up to 0.91.

Keywords: immature palm count, oil palm, precision agriculture, remote sensing

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Authors: Magdy Roman, Mostafa Shoeib, Mostafa Rostom

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Global vision, whether provided by overhead fixed cameras, on-board aerial vehicle cameras, or satellite images can always provide detailed information on the environment around mobile robots. In this paper, an intelligent vision-based method of path planning and obstacle avoidance for mobile robots is presented. The method integrates visual perception with a new proposed field-based path-planning method to overcome common path-planning problems such as local minima, unreachable destination and unnecessary lengthy paths around obstacles. The method proposes an exponential angle deviation field around each obstacle that affects the orientation of a close robot. As the robot directs toward, the goal point obstacles are classified into right and left groups, and a deviation angle is exponentially added or subtracted to the orientation of the robot. Exponential field parameters are chosen based on Lyapunov stability criterion to guarantee robot convergence to the destination. The proposed method uses obstacles' shape and location, extracted from global vision system, through a collision prediction mechanism to decide whether to activate or deactivate obstacles field. In addition, a search mechanism is developed in case of robot or goal point is trapped among obstacles to find suitable exit or entrance. The proposed algorithm is validated both in simulation and through experiments. The algorithm shows effectiveness in obstacles' avoidance and destination convergence, overcoming common path planning problems found in classical methods.

Keywords: path planning, collision avoidance, convergence, computer vision, mobile robots

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Authors: Muhammad Usman Akram

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This research work based on GNSS-Aided Photogrammetry for Digital Mapping. It focuses on topographic survey of an area or site which is to be used in future Planning & development (P&D) or can be used for further, examination, exploration, research and inspection. Survey and Mapping in hard-to-access and hazardous areas are very difficult by using traditional techniques and methodologies; as well it is time consuming, labor intensive and has less precision with limited data. In comparison with the advance techniques it is saving with less manpower and provides more precise output with a wide variety of multiple data sets. In this experimentation, Aerial Photogrammetry technique is used where an UAV flies over an area and captures geocoded images and makes a Three-Dimensional Model (3-D Model), UAV operates on a user specified path or area with various parameters; Flight altitude, Ground sampling distance (GSD), Image overlapping, Camera angle etc. For ground controlling, a network of points on the ground would be observed as a Ground Control point (GCP) using Differential Global Positioning System (DGPS) in PPK or RTK mode. Furthermore, that raw data collected by UAV and DGPS will be processed in various Digital image processing programs and Computer Aided Design software. From which as an output we obtain Points Dense Cloud, Digital Elevation Model (DEM) and Ortho-photo. The imagery is converted into geospatial data by digitizing over Ortho-photo, DEM is further converted into Digital Terrain Model (DTM) for contour generation or digital surface. As a result, we get Digital Map of area to be surveyed. In conclusion, we compared processed data with exact measurements taken on site. The error will be accepted if the amount of error is not breached from survey accuracy limits set by concerned institutions.

Keywords: photogrammetry, post processing kinematics, real time kinematics, manual data inquiry

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Authors: Mostafa Mjahed

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This paper concerns the control of a nonlinear system using two different methods, reference model and genetic algorithm. The quadcopter is a nonlinear unstable system, which is a part of aerial robots. It is constituted by four rotors placed at the end of a cross. The center of this cross is occupied by the control circuit. Its motions are governed by six degrees of freedom: three rotations around 3 axes (roll, pitch and yaw) and the three spatial translations. The control of such system is complex, because of nonlinearity of its dynamic representation and the number of parameters, which it involves. Numerous studies have been developed to model and stabilize such systems. The classical PID and LQ correction methods are widely used. If the latter represent the advantage to be simple because they are linear, they reveal the drawback to require the presence of a linear model to synthesize. It also implies the complexity of the established laws of command because the latter must be widened on all the domain of flight of these quadcopter. Note that, if the classical design methods are widely used to control aeronautical systems, the Artificial Intelligence methods as genetic algorithms technique receives little attention. In this paper, we suggest comparing two PID design methods. Firstly, the parameters of the PID are calculated according to the reference model. In a second phase, these parameters are established using genetic algorithms. By reference model, we mean that the corrected system behaves according to a reference system, imposed by some specifications: settling time, zero overshoot etc. Inspired from the natural evolution of Darwin's theory advocating the survival of the best, John Holland developed this evolutionary algorithm. Genetic algorithm (GA) possesses three basic operators: selection, crossover and mutation. We start iterations with an initial population. Each member of this population is evaluated through a fitness function. Our purpose is to correct the behavior of the quadcopter around three axes (roll, pitch and yaw) with 3 PD controllers. For the altitude, we adopt a PID controller.

Keywords: quadcopter, genetic algorithm, PID, fitness, model, control, nonlinear system

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Authors: Maira C. M. Fonseca, Maria Aparecida N. Sediyama, Rosana Goncalves R. das Dores, Sanzio Mollica Vidigal, Alberto C. P. Dias

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Among Brazilian plant diversity, many species are used as food and considered minor crops (non-conventional plant foods) (NCPF). Arrowroot (Maranta arundinacea) is a NCPF from which starch is extracted from rhizome do not have gluten. Thus, arrowroot flower starch can be consumed by celiac people. Additional, some medicinal and functional proprieties are assigned to arrowroot leaves which currently are underutilized. In Brazil, it’s cultivated mainly by small scale farmers and there is no specific recommendation for fertilization. This work aimed to determinate the best fertilization for rhizome production and to verify its influence in phenolic composition and antioxidant activity of leaf extracts. Two arrowroot varieties, “Common” and “Seta”, were cultivated in organic system at state of Minas Gerais, Brazil, using cattle manure with three levels of nitrogen (N) (0, 300 and 900 kg N ha-1). The experiment design was in randomized block with four replicates. The highest production of rhizomes in both varieties, “Common” (38198.24 kg ha-1) and “Seta” (43567.71 kg ha-1), were obtained with the use of 300 kg N ha-1. With this fertilization, the total aerial part, petiole and leaf production in the varieties were respectively: “Common” (190.312 kg ha-1; 159.312 kg ha-1; 31.100 kg ha-1) and “Seta” (207.656 kg ha-1; 180.539 kg ha-1; 27.062 kg ha-1). Methanolic leaf extracts were analysed by HPLC-DAD. The major phenolic compounds found were caffeioylquinic acids, p-coumaric derivatives and flavonoids. In general, the production of these compounds significantly decreases with the increase levels of nitrogen (900 kg N ha-1). With 300 kg N ha-1 the phenolic production was similar to control. The antioxidant activity was evaluated using DPPH method and was detected around 60% of radical scavenging when 0.1 mg/mL of plant extracts were used. We concluded that fertilization with 300 kg N ha-1 increased arrowroot rhizome production, maintaining phenolic compounds yield at leaves.

Keywords: antioxidant activity, non-conventional plants, organic fertilization, phenolic compounds

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Authors: Jaypalsinh Parmar, Pintu Nakrani, Bhaumik Shah

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Digital Elevation Model (DEM) is elevation data of the virtual grid on the ground. DEM can be used in application in GIS such as hydrological modelling, flood forecasting, morphometrical analysis and surveying etc.. For morphometrical analysis the stream flow network plays a very important role. DEM lacks accuracy and cannot match field data as it should for accurate results of morphometrical analysis. The present study focuses on comparing the Agree method and the conventional Shortest path method for finding out morphometric parameters in the flat region of the Lower Tapi Basin which is located in the western India. For the present study, open source SRTM (Shuttle Radar Topography Mission with 1 arc resolution) and toposheets issued by Survey of India (SOI) were used to determine the morphometric linear aspect such as stream order, number of stream, stream length, bifurcation ratio, mean stream length, mean bifurcation ratio, stream length ratio, length of overland flow, constant of channel maintenance and aerial aspect such as drainage density, stream frequency, drainage texture, form factor, circularity ratio, elongation ratio, shape factor and relief aspect such as relief ratio, gradient ratio and basin relief for 53 catchments of Lower Tapi Basin. Stream network was digitized from the available toposheets. Agree DEM was created by using the SRTM and stream network from the toposheets. The results obtained were used to demonstrate a comparison between the two methods in the flat areas.

Keywords: agree method, morphometric analysis, lower Tapi basin, shortest path method

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Authors: Karem H. Alzoubi, Ahmad S. Alkofahi, Omar F. Khabour, Nizar M. Mhaidat

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Herbal medicinal products represent a major focus for drug development and industry and it holds a significant share in drug-market all over the globe. In here, selected medicinal plant extracts from Jordan with high antioxidative capacity were tested for their protective effect against oxidative DNA damage using in vitro 8-hydroxydeoxyguanisine and sister chromatid exchanges (SCEs) assays in cultured human lymphocytes. The following plant extracts were tested Cupressus sempervirens L., Psidium guajava (L.) Gaerth., Silybum marianum L., Malva sylvestris L., Varthemia iphionoides Boiss., Eminium spiculatum L. Blume, Pistachia palaestina Boiss., Artemisia herba-alba Asso, Ficus carica L., Morus alba Linn , Cucumis sativus L., Eucalyptus camaldulensis Dehnh., Salvia triloba L., Zizyphus spina-christi L. Desf., and Laurus nobilis L. A fractionation scheme for the active plant extracts of the above was followed. Plants extract fractions with best protective properties against DNA damage included hexane fraction of S. marianum L. (aerial parts), chloroform fractions of P. palaestina Boiss. (Fruits), ethanolic fractions of E. camaldulensis Dehnh (leaves), S. triloba L. (leaves), and ethanolic fractions of Z. spina-christi L. Desf. (Fruits/leaves). On the other hand, the ethanolic extracts of V. iphionoides Boiss was found to increase oxidative DNA damage. Results of the SCEs are undergoing. In conclusion, plant extracts with antioxidative DNA damage properties might have clinical applications in cancer prevention.

Keywords: medicinal plants extract, fractionation, oxidative DNA damage, 8-hydroxydeoxyguanisine, SCEs, Jordan

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Authors: I GD Yudha Partama, A. Kanno, Y. Akamatsu, R. Inui, M. Goto, M. Sekine

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The aerial photogrammetry of shallow water bottoms has the potential to be an efficient high-resolution survey technique for shallow water topography, thanks to the advent of convenient UAV and automatic image processing techniques Structure-from-Motion (SfM) and Multi-View Stereo (MVS)). However, it suffers from the systematic overestimation of the bottom elevation, due to the light refraction at the air-water interface. In this study, we present an empirical method to correct for the effect of refraction after the usual SfM-MVS processing, using common software. The presented method utilizes the empirical relation between the measured true depth and the estimated apparent depth to generate an empirical correction factor. Furthermore, this correction factor was utilized to convert the apparent water depth into a refraction-corrected (real-scale) water depth. To examine its effectiveness, we applied the method to two river sites, and compared the RMS errors in the corrected bottom elevations with those obtained by three existing methods. The result shows that the presented method is more effective than the two existing methods: The method without applying correction factor and the method utilizes the refractive index of water (1.34) as correction factor. In comparison with the remaining existing method, which used the additive terms (offset) after calculating correction factor, the presented method performs well in Site 2 and worse in Site 1. However, we found this linear regression method to be unstable when the training data used for calibration are limited. It also suffers from a large negative bias in the correction factor when the apparent water depth estimated is affected by noise, according to our numerical experiment. Overall, the good accuracy of refraction correction method depends on various factors such as the locations, image acquisition, and GPS measurement conditions. The most effective method can be selected by using statistical selection (e.g. leave-one-out cross validation).

Keywords: bottom elevation, MVS, river, SfM

Procedia PDF Downloads 299