Search results for: spatial variation

Authors: Jigg Pelayo, Ricardo Villar

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The Philippines is long considered as a valuable producer of high value crops globally. The country’s employment and economy have been dependent on agriculture, thus increasing its demand for the efficient agricultural mechanism. Remote sensing and geographic information technology have proven to effectively provide applications for precision agriculture through image-processing technique considering the development of the aerial scanning technology in the country. Accurate information concerning the spatial correlation within the field is very important for precision farming of high value crops, especially. The availability of height information and high spatial resolution images obtained from aerial scanning together with the development of new image analysis methods are offering relevant influence to precision agriculture techniques and applications. In this study, an algorithm was developed and implemented to detect and count high value crops simultaneously through adaptive scaling of support vector machine (SVM) algorithm subjected to object-oriented approach combining watershed transformation and local maxima filter in enhancing tree counting and detection. The methodology is compared to cutting-edge template matching algorithm procedures to demonstrate its effectiveness on a demanding tree is counting recognition and delineation problem. Since common data and image processing techniques are utilized, thus can be easily implemented in production processes to cover large agricultural areas. The algorithm is tested on high value crops like Palm, Mango and Coconut located in Misamis Oriental, Philippines - showing a good performance in particular for young adult and adult trees, significantly 90% above. The s inventories or database updating, allowing for the reduction of field work and manual interpretation tasks.

Keywords: high value crop, LiDAR, OBIA, precision agriculture

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Authors: Rafay Ahmed, Condon Lau

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Bone healing is a complex and sequential process involving changes at the molecular level. Raman spectroscopy is a promising technique to study bone mineral and matrix environments simultaneously. In this study, subcritical calvarial defects are used to study bone composition during healing without discomposing the fracture. The model allowed to monitor the natural healing of bone avoiding mechanical harm to the callus. Calvarial defects were created using 1mm burr drill in the parietal bones of Sprague-Dawley rats (n=8) that served in vivo defects. After 7 days, their skulls were harvested after euthanizing. One additional defect per sample was created on the opposite parietal bone using same calvarial defect procedure to serve as control defect. Raman spectroscopy (785 nm) was established to investigate bone parameters of three different skull surfaces; in vivo defects, control defects and normal surface. Principal component analysis (PCA) was utilized for the data analysis and interpretation of Raman spectra and helped in the classification of groups. PCA was able to distinguish in vivo defects from normal surface and control defects. PC1 shows that the major variation at 958 cm⁻¹, which corresponds to ʋ1 phosphate mineral band. PC2 shows the major variation at 1448 cm⁻¹ which is the characteristic band of CH2 deformation and corresponds to collagens. Raman parameters, namely, mineral to matrix ratio and crystallinity was found significantly decreased in the in vivo defects compared to surface and controls. Scanning electron microscope and optical microscope images show the formation of newly generated matrix by means of bony bridges of collagens. Optical profiler shows that surface roughness increased by 30% from controls to in vivo defects after 7 days. These results agree with Raman assessment parameters and confirm the new collagen formation during healing.

Keywords: Raman spectroscopy, principal component analysis, calvarial defects, tissue characterization

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Authors: Jia Li, Xing Wei, Yuchen Hong, Yang Lu

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Detecting vehicle behavior has always been the focus of intelligent transportation, but with the explosive growth of the number of vehicles and the complexity of the road environment, the vehicle behavior videos captured by traditional surveillance have been unable to satisfy the study of vehicle behavior. The traditional method of manually labeling vehicle behavior is too time-consuming and labor-intensive, but the existing object detection and tracking algorithms have poor practicability and low behavioral location detection rate. This paper proposes a vehicle behavior detection algorithm based on the dual-stream convolution network and the multi-dimensional video dynamic detection network. In the videos, the straight-line behavior of the vehicle will default to the background behavior. The Changing lanes, turning and turning around are set as target behaviors. The purpose of this model is to automatically mark the target behavior of the vehicle from the untrimmed videos. First, the target behavior proposals in the long video are extracted through the dual-stream convolution network. The model uses a dual-stream convolutional network to generate a one-dimensional action score waveform, and then extract segments with scores above a given threshold M into preliminary vehicle behavior proposals. Second, the preliminary proposals are pruned and identified using the multi-dimensional video dynamic detection network. Referring to the hierarchical reinforcement learning, the multi-dimensional network includes a Timer module and a Spacer module, where the Timer module mines time information in the video stream and the Spacer module extracts spatial information in the video frame. The Timer and Spacer module are implemented by Long Short-Term Memory (LSTM) and start from an all-zero hidden state. The Timer module uses the Transformer mechanism to extract timing information from the video stream and extract features by linear mapping and other methods. Finally, the model fuses time information and spatial information and obtains the location and category of the behavior through the softmax layer. This paper uses recall and precision to measure the performance of the model. Extensive experiments show that based on the dataset of this paper, the proposed model has obvious advantages compared with the existing state-of-the-art behavior detection algorithms. When the Time Intersection over Union (TIoU) threshold is 0.5, the Average-Precision (MP) reaches 36.3% (the MP of baselines is 21.5%). In summary, this paper proposes a vehicle behavior detection model based on multi-dimensional dynamic detection network. This paper introduces spatial information and temporal information to extract vehicle behaviors in long videos. Experiments show that the proposed algorithm is advanced and accurate in-vehicle timing behavior detection. In the future, the focus will be on simultaneously detecting the timing behavior of multiple vehicles in complex traffic scenes (such as a busy street) while ensuring accuracy.

Keywords: vehicle behavior detection, convolutional neural network, long short-term memory, deep learning

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Authors: Ali Reza Vaezi, Naser Fakori Ivand, Fereshteh Azarifam

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Interrill erosion is the detachment and transfer of soil particles between the rills due to the impact of raindrops and the shear stress of shallow surface runoff. This erosion can be affected by some soil properties such as texture, amount of organic matter and stability of soil aggregates. Information on the temporal variation of interrill erosion during a rainfall event and the effect soil properties have on it can help in understanding the process of runoff production and soil loss between the rills in hillslopes. The importance of this study is especially grate in semi-arid regions, where the soil is weakly aggregated and vegetation cover is mostly poor. Therefore, this research was conducted to investigate the temporal variation of surface flow and interrill erosion and the effect of soil properties on it in some semi-arid soils. A field experiment was done in eight different soil textures under simulated rainfalls with uniform intensity. A total of twenty four plots were installed for eight study soils with three replicates in the form of a random complete block design along the land. The plots were 1.2 m (length) × 1 m (width) in dimensions which designed with a distance of 3 m from each other across the slope. Then, soil samples were purred into the plots. The plots were surrounded by a galvanized sheet, and runoff and soil erosion equipment were placed at their outlets. Rainfall simulation experiments were done using a designed portable simulator with an intensity of 60 mm per hour for 60 minutes. A plastic cover was used around the rainfall simulator frame to prevent the impact of the wind on the free fall of water drops. Runoff production and soil loss were measured during 1 hour time with 5-min intervals. In order to study soil properties, such as particle size distribution, aggregate stability, bulk density, ESP and Ks were determined in the laboratory. Correlation and regression analysis was done to determine the effect of soil properties on runoff and interrill erosion. Results indicated that the study soils have lower booth organic matter content and aggregate stability. The soils, except for coarse textured textures, are calcareous and with relatively higher exchangeable sodium percentages (ESP). Runoff production and soil loss didn’t occur in sand, which was associated with higher infiltration and drainage rates. In other study soils, interrill erosion occurred simultaneously with the generation of runoff. A strong relationship was found between interrill erosion and surface runoff (R2 = 0.75, p< 0.01). The correlation analysis showed that surface runoff was significantly affected by some soil properties consisting of sand, silt, clay, bulk density, gravel, hydraulic conductivity (Ks), lime (calcium carbonate), and ESP. The soils with lower Ks such as fine-textured soils, produced higher surface runoff and more interrill erosion. In the soils, Surface runoff production temporally increased during rainfall and finally reached a peak after about 25-35 min. Time to peak was very short (30 min) in fine-textured soils, especially clay, which was related to their lower infiltration rate.

Keywords: erosion plot, rainfall simulator, soil properties, surface flow

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Authors: Reema Tiwari, U. C. Kulshrestha

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As a key regulator of atmospheric oxidative capacity and secondary aerosol formations, the signatures of reactive nitrogen (Nr) emissions are becoming increasingly evident in the cascade of air pollution, acidification, and eutrophication of the ecosystem. However, their accurate estimates in N budget remains limited by the photochemical conversion processes where occurrence of differential atmospheric residence time of gaseous (NOₓ, HNO₃, NH₃) and particulate (NO₃⁻, NH₄⁺) Nr species becomes imperative to their spatio temporal evolution on a synoptic scale. The present study attempts to quantify such interactions under tropical conditions when low anticyclonic winds become favorable to the advections from west during winters. For this purpose, a diurnal sampling was conducted using low volume sampler assembly where ambient concentrations of Nr trace gases along with their ionic fractions in the aerosol samples were determined with UV-spectrophotometer and ion chromatography respectively. The results showed a spatial gradient of the gaseous precursors with a much pronounced inter site variability (p < 0.05) than their particulate fractions. Such observations were confirmed for their limited photochemical conversions where less than 1 ratios of day and night measurements (D/N) for the different Nr fractions suggested an influence of boundary layer dynamics at the background site. These phase conversion processes were further corroborated with the molar ratios of NOₓ/NOᵧ and NH₃/NHₓ where incomplete titrations of NOₓ and NH₃ emissions were observed irrespective of their diurnal phases along the sampling transect. Their calculations with equilibrium based approaches for an NH₃-HNO₃-NH₄NO₃ system, on the other hand, were characterized by delays in equilibrium attainment where plots of their below deliquescence Kₘ and Kₚ values with 1000/T confirmed the role of lower temperature ranges in NH₄NO₃ aerosol formation. These results would help us in not only resolving the changing atmospheric inputs of reduced (NH₃, NH₄⁺) and oxidized (NOₓ, HNO₃, NO₃⁻) Nr estimates but also in understanding the dependence of Nr mixing ratios on their local meteorological conditions.

Keywords: diurnal ratios, gas-aerosol interactions, spatial gradient, thermodynamic equilibrium

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Authors: Yannay Casas-Ledon, Cinthya A. Andrade, Camila E. Salazar, Mauricio Aguayo

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The sustainable management of available natural resources is a crucial question for policy-makers, economists, and the research community. Among several, land constitutes one of the most critical resources, which is being intensively appropriated by human activities producing ecological stresses and reducing ecosystem services. In this context, net primary production (NPP) has been considered as a feasible proxy indicator for estimating the impacts of human interventions on land-uses intensity. Accordingly, the human appropriation of NPP (HANPP) was calculated for the south-central regions of Chile between 2007 and 2014. The HANPP was defined as the difference between the potential NPP of the naturally produced vegetation (NPP0, i.e., the vegetation that would exist without any human interferences) and the NPP remaining in the field after harvest (NPPeco), expressed in gC/m² yr. Other NPP flows taken into account in HANPP estimation were the harvested (NPPh) and the losses of NPP through land conversion (NPPluc). The ArcGIS 10.4 software was used for assessing the spatial and temporal HANPP changes. The differentiation of HANPP as % of NPP0 was estimated by each landcover type taken in 2007 and 2014 as the reference years. The spatial results depicted a negative impact on land use efficiency during 2007 and 2014, showing negative HANPP changes for the whole region. The harvest and biomass losses through land conversion components are the leading causes of loss of land-use efficiency. Furthermore, the study depicted higher HANPP in 2014 than in 2007, representing 50% of NPP0 for all landcover classes concerning 2007. This performance was mainly related to the higher volume of harvested biomass for agriculture. In consequence, the cropland depicted the high HANPP followed by plantation. This performance highlights the strong positive correlation between the economic activities developed into the region. This finding constitutes the base for a better understanding of the main driving force influencing biomass productivity and a powerful metric for supporting the sustainable management of land use.

Keywords: human appropriation, land-use changes, land-use impact, net primary productivity

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Authors: Angela Oktavia Suryani, Bernadeth Gloria, Edwin Sutamto, Jessica Kristianty, Ni Made Rai Sapitri, Patricia Catherine Agla, Sitti Arlinda Rochiadi

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It was found that some blogs or personal websites in Indonesia sell standardized intelligence tests (for example, Progressive Matrices (PM), Intelligence Structure Test (IST), and Culture Fair Intelligence Test (CFIT)) and other psychological tests, together with the manual and the key answers for public. Individuals can buy and prepare themselves for selection or recruitment with the real test. This action drives people to lie to the institution (education or company) and also to themselves. It was also found that those tests are old. Some items are not relevant with the current context, for example a question about a diameter of a certain coin that does not exist anymore. These problems motivate us to develop a new intelligence battery test, namely of Multiple Aptitude Battery (MAB). The battery test was built by using Thurstone’s Primary Mental Abilities theory and intended to be used by high schools students, university students, and worker applicants. The battery tests consist of 9 subtests. In the current study we examine six subtests, namely Reading Comprehension, Verbal Analogies, Numerical Inductive Reasoning, Numerical Deductive Reasoning, Mechanical Ability, and Two Dimensional Spatial Reasoning for university students. The study included 1424 data from students recruited by convenience sampling from eight faculties at Atma Jaya Catholic University of Indonesia. Classical and modern test approaches (Item Response Theory) were carried out to identify the item difficulties of the items and confirmatory factor analysis was applied to examine their internal validities. The validity of each subtest was inspected by using convergent–discriminant method, whereas the reliability was examined by implementing Kuder–Richardson formula. The result showed that the majority of the subtests were difficult in medium level, and there was only one subtest categorized as easy, namely Verbal Analogies. The items were found homogenous and valid measuring their constructs; however at the level of subtests, the construct validity examined by convergent-discriminant method indicated that the subtests were not unidimensional. It means they were not only measuring their own constructs but also other construct. Three of the subtests were able to predict academic performance with small effect size, namely Reading Comprehension, Numerical Inductive Reasoning, and Two Dimensional Spatial Reasoning. GPAs in intermediate level (GPAs at third semester and above) were considered as a factor for predictive invalidity. The Kuder-Richardson formula showed that the reliability coefficients for both numerical reasoning subtests and spatial reasoning were superior, in the range 0.84 – 0.87, whereas the reliability coefficient for the other three subtests were relatively below standard for ability test, in the range of 0.65 – 0.71. It can be concluded that some of the subtests are ready to be used, whereas some others are still need some revisions. This study also demonstrated that the convergent-discrimination method is useful to identify the general intelligence of human.

Keywords: intelligence, psychometric examination, multiple aptitude battery, university students

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Authors: B. Mavhuru, N. S. Nethengwe

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Human activities on land degradation have triggered several environmental problems especially in rural areas that are underdeveloped. The main aim of this study is to analyze the contribution of different land uses to gully development and sediment load on the Nzhelele River Valley in the Limpopo Province. Data was collected using different methods such as observation, field data techniques and experiments. Satellite digital images, topographic maps, aerial photographs and the sediment load static model also assisted in determining how land use affects gully development and sediment load. For data analysis, the researcher used the following methods: Analysis of Variance (ANOVA), descriptive statistics, Pearson correlation coefficient and statistical correlation methods. The results of the research illustrate that high land use activities create negative changes especially in areas that are highly fragile and vulnerable. Distinct impact on land use change was observed within settlement area (9.6 %) within a period of 5 years. High correlation between soil organic matter and soil moisture (R=0.96) was observed. Furthermore, a significant variation (p ≤ 0.6) between the soil organic matter and soil moisture was also observed. A very significant variation (p ≤ 0.003) was observed in bulk density and extreme significant variations (p ≤ 0.0001) were observed in organic matter and soil particle size. The sand mining and agricultural activities has contributed significantly to the amount of sediment load in the Nzhelele River. A high significant amount of total suspended sediment (55.3 %) and bed load (53.8 %) was observed within the agricultural area. The connection which associates the development of gullies to various land use activities determines the amount of sediment load. These results are consistent with other previous research and suggest that land use activities are likely to exacerbate the development of gullies and sediment load in the Nzhelele River Valley.

Keywords: drainage basin, geomorphological processes, gully development, land degradation, riparian land use and sediment load

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Authors: Christopher Restall

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field causing attraction between mixed charges of matter during charge exchanges with antimatter. This asymmetry is caused from none-trinary quark amount variation in matter and anti-matter during entropy progression. This document explains how a circularity critique exercise assessed scientific knowledge and develop a unified theory from the information collected. The circularity critique, creates greater intuition leaps than an individual would naturally, the information collected can be integrated and assessed thoroughly for correctness.

Keywords: unified theory of everything, gravity, quantum gravity, standard model

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Authors: Oliver Ikechukwu Inyiama, Boniface Uche Ugwuanyi

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The aim of the research is to evaluate the key financial performance indicators that help both managers and their shareholders of Nigerian Banks to determine the appropriate dividend payout to their ordinary shareholders in an accounting year. Profitability, total asset, and earnings of commercial banks were selected as key performance indicators in Nigeria Banking Sector. They represent the independent variables of the study while dividend per share is the proxy for the dividend paid on ordinary shares which represent the dependent variable. The effect of profitability, total asset and earnings on dividend per share were evaluated through the ordinary least square method of multiple regression analysis. Test for normality of frequency distribution was conducted through descriptive statistics such as Jacque Bera Statistic, skewness and kurtosis. Rate of dividend payout was subsequently applied as an alternate dependent variable to test for robustness of the earlier results. The 64% adjusted R-squared of the pooled data indicates that profitability, total asset, and earnings explain the variation in dividend per share during the period under research while the remaining 36% variation in dividend per share could be explained by changes in other variables not captured by this study as well as the error term. The study concentrated on four leading Nigeria Commercial Banks namely; First Bank of Nigeria Plc, GTBank Plc, United Bank for Africa Plc and Zenith International Bank Plc. Dividend per share was found to be positively affected by total assets and earnings of the commercial banks. However, profitability which was proxied by profit after tax had a negative effect on dividend per share. The implication of the findings is that commercial banks in Nigeria pay more dividend when they are having a dwindling fortune in order to retain the confidence of the shareholders provided their gross earnings and size is on the increase. Therefore, the management and board of directors of Nigeria commercial banks should apply decent marketing strategies to enhance earnings through investment in profitable ventures for an improved dividend payout rate.

Keywords: assets, banks, indicators, performance, profitability, shares

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Authors: Nurcihan Kiris

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Restricted sleep is common in young adults and adolescents. The results of a few objective studies of sleep deprivation on cognitive performance were not clarified. In particular, the effect of sleep deprivation on the cognitive functions associated with frontal lobe such as attention, executive functions, working memory is not well known. The aim of this study is to investigate the effect of partial sleep deprivation experimentally in adolescents on the cognitive tasks of frontal lobe including working memory, strategic thinking, simple attention, continuous attention, executive functions, and cognitive flexibility. Subjects of the study were recruited from voluntary students of Cukurova University. Eighteen adolescents underwent four consecutive nights of monitored sleep restriction (6–6.5 hr/night) and four nights of sleep extension (10–10.5 hr/night), in counterbalanced order, and separated by a washout period. Following each sleep period, cognitive performance was assessed, at a fixed morning time, using a computerized neuropsychological battery based on frontal lobe functions task, a timed test providing both accuracy and reaction time outcome measures. Only the spatial working memory performance of cognitive tasks was found to be statistically lower in a restricted sleep condition than the extended sleep condition. On the other hand, there was no significant difference in the performance of cognitive tasks evaluating simple attention, constant attention, executive functions, and cognitive flexibility. It is thought that especially the spatial working memory and strategic thinking skills of adolescents may be susceptible to sleep deprivation. On the other hand, adolescents are predicted to be optimally successful in ideal sleep conditions, especially in the circumstances requiring for the short term storage of visual information, processing of stored information, and strategic thinking. The findings of this study may also be associated with possible negative functional effects on the processing of academic social and emotional inputs in adolescents for partial sleep deprivation. Acknowledgment: This research was supported by Cukurova University Scientific Research Projects Unit.

Keywords: attention, cognitive functions, sleep deprivation, working memory

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Authors: Pulakesh Das, Mukunda Dev Behera, Manchiraju Sri Ramachandra Murthy

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Large numbers of people living in and around the Hindu Kush Himalaya (HKH) region, depends on this diverse mountainous region for ecosystem services. Following the global trend, this region also experiencing rapid population growth, and demand for timber and agriculture land. The eight countries sharing the HKH region have different forest resources utilization and conservation policies that exert varying forces in the forest ecosystem. This created a variable spatial as well altitudinal gradient in rate of deforestation and corresponding forest patch fragmentation. The quantitative relationship between fragmentation and demography has not been established before for HKH vis-à-vis along elevation gradient. This current study was carried out to attribute the overall and different nature in landscape fragmentations along the altitudinal gradient with the demography of each sharing countries. We have used the tree canopy cover data derived from Landsat data to analyze the deforestation and afforestation rate, and corresponding landscape fragmentation observed during 2000 – 2010. Area-weighted mean radius of gyration (AMN radius of gyration) was computed owing to its advantage as spatial indicator of fragmentation over non-spatial fragmentation indices. Using the subtraction method, the change in fragmentation was computed during 2000 – 2010. Using the tree canopy cover data as a surrogate of forest cover, highest forest loss was observed in Myanmar followed by China, India, Bangladesh, Nepal, Pakistan, Bhutan, and Afghanistan. However, the sequence of fragmentation was different after the maximum fragmentation observed in Myanmar followed by India, China, Bangladesh, and Bhutan; whereas increase in fragmentation was seen following the sequence of as Nepal, Pakistan, and Afghanistan. Using SRTM-derived DEM, we observed higher rate of fragmentation up to 2400m that corroborated with high human population for the year 2000 and 2010. To derive the nature of fragmentation along the altitudinal gradients, the Statistica software was used, where the user defined function was utilized for regression applying the Gauss-Newton estimation method with 50 iterations. We observed overall logarithmic decrease in fragmentation change (area-weighted mean radius of gyration), forest cover loss and population growth during 2000-2010 along the elevation gradient with very high R2 values (i.e., 0.889, 0.895, 0.944 respectively). The observed negative logarithmic function with the major contribution in the initial elevation gradients suggest to gap filling afforestation in the lower altitudes to enhance the forest patch connectivity. Our finding on the pattern of forest fragmentation and human population across the elevation gradient in HKH region will have policy level implication for different nations and would help in characterizing hotspots of change. Availability of free satellite derived data products on forest cover and DEM, grid-data on demography, and utility of geospatial tools helped in quick evaluation of the forest fragmentation vis-a-vis human impact pattern along the elevation gradient in HKH.

Keywords: area-weighted mean radius of gyration, fragmentation, human impact, tree canopy cover

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Authors: R. Lhissou , A. El Harti , K. Chokmani, E. Bachaoui, A. El Ghmari

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Soil salinity is a serious environmental hazard in many countries around the world especially the arid and semi-arid countries like Morocco. Salinization causes negative effects on the ground; it affects agricultural production, infrastructure, water resources and biodiversity. Remote sensing can provide soil salinity information for large areas, and in a relatively short time. In addition, remote sensing is not limited by extremes in terrain or hazardous condition. Contrariwise, experimental methods for monitoring soil salinity by direct measurements in situ are very demanding of time and resources, and also very limited in spatial coverage. In the irrigated perimeter of Tadla plain in central Morocco, the increased use of saline groundwater and surface water, coupled with agricultural intensification leads to the deterioration of soil quality especially by salinization. In this study, we assessed several spectral indices of soil salinity cited in the literature using Landsat TM satellite images and field measurements of electrical conductivity (EC). Three Landsat TM satellite images were taken during 3 months in the dry season (September, October and November 2011). Based on field measurement data of EC collected in three field campaigns over the three dates simultaneously with acquisition dates of Landsat TM satellite images, a two assessment techniques are used to validate a soil salinity spectral indices. Firstly, the spectral indices are validated locally by pixel. The second validation technique is made using a window of size 3x3 pixels. The results of the study indicated that the second technique provides getting a more accurate validation and the assessment has shown its limits when it comes to assess across the pixel. In addition, the EC values measured from field have a good correlation with some spectral indices derived from Landsat TM data and the best results show an r² of 0.88, 0.79 and 0.65 for Salinity Index (SI) in the three dates respectively. The results have shown the usefulness of spectral indices as an auxiliary variable in the spatial estimation and mapping salinity in irrigated land.

Keywords: remote sensing, spectral indices, soil salinity, irrigated land

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Authors: Faisal G. Khamis, Ghaleb A. El-Refae

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Many researchers have studied socioeconomic, health, and security variables in the developed countries; however, very few studies used multivariate analysis in developing countries. The current study contributes to the scarce literature about the determinants of the variance in socioeconomic, health, and security factors. Questions raised were whether the independent variables (IVs) of governorate and year impact the socioeconomic, health, and security dependent variables (DVs) in Jordan, whether the marginal mean of each DV in each governorate and in each year is significant, which governorates are similar in difference means of each DV, and whether these DVs vary. The main objectives were to determine the source of variances in DVs, collectively and separately, testing which governorates are similar and which diverge for each DV. The research design was time series and cross-sectional analysis. The main hypotheses are that IVs affect DVs collectively and separately. Multivariate and univariate analyses of variance were carried out to test these hypotheses. The population of 12 governorates in Jordan and the available data of 15 years (2000–2015) accrued from several Jordanian statistical yearbooks. We investigated the effect of two factors of governorate and year on the four DVs of divorce rate, mortality rate, unemployment percentage, and crime rate. All DVs were transformed to multivariate normal distribution. We calculated descriptive statistics for each DV. Based on the multivariate analysis of variance, we found a significant effect in IVs on DVs with p < .001. Based on the univariate analysis, we found a significant effect of IVs on each DV with p < .001, except the effect of the year factor on unemployment was not significant with p = .642. The grand and marginal means of each DV in each governorate and each year were significant based on a 95% confidence interval. Most governorates are not similar in DVs with p < .001. We concluded that the two factors produce significant effects on DVs, collectively and separately. Based on these findings, the government can distribute its financial and physical resources to governorates more efficiently. By identifying the sources of variance that contribute to the variation in DVs, insights can help inform focused variation prevention efforts.

Keywords: ANOVA, crime, divorce, governorate, hypothesis test, Jordan, MANOVA, means, mortality, unemployment, year

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Authors: I. Asanuma, T. Yamaguchi, J. Park, K. J. Mackin

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Fishery lights on the surface could be detected by the Day and Night Band (DNB) of the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership (Suomi-NPP). The DNB covers the spectral range of 500 to 900 nm and realized a higher sensitivity. The DNB has a difficulty of identification of fishing lights from lunar lights reflected by clouds, which affects observations for the half of the month. Fishery lights and lights of the surface are identified from lunar lights reflected by clouds by a method using the DNB and the infrared band, where the detection limits are defined as a function of the brightness temperature with a difference from the maximum temperature for each level of DNB radiance and with the contrast of DNB radiance against the background radiance. Fishery boats or structures on islands could be detected by the Synthetic Aperture Radar (SAR) on the polar orbit satellites using the reflected microwave by the surface reflecting targets. The SAR has a difficulty of tradeoff between spatial resolution and coverage while detecting the small targets like fishery boats. A distribution of fishery boats and island activities were detected by the scan-SAR narrow mode of Radarsat-2, which covers 300 km by 300 km with various combinations of polarizations. The fishing boats were detected as a single pixel of highly scattering targets with the scan-SAR narrow mode of which spatial resolution is 30 m. As the look angle dependent scattering signals exhibits the significant differences, the standard deviations of scattered signals for each look angles were taken into account as a threshold to identify the signal from fishing boats and structures on the island from background noise. It was difficult to validate the detected targets by DNB with SAR data because of time lag of observations for 6 hours between midnight by DNB and morning or evening by SAR. The temporal changes of island activities were detected as a change of mean intensity of DNB for circular area for a certain scale of activities. The increase of DNB mean intensity was corresponding to the beginning of dredging and the change of intensity indicated the ending of reclamation and following constructions of facilities.

Keywords: day night band, SAR, fishery, South China Sea

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Authors: I. Georgousopoulou, S. Vouyiouka, C. Papaspyrides

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The hydrolytic degradation of poly(butylene succinate) (PBS) was investigated when exposed to different humidity-temperature environments. To this direction different PBS grades were submitted to hydrolysis runs. Results indicated that the increment of hydrolysis temperature and relative humidity induced significant decrease in the molecular weight and thermal properties of the bioplastic. Τhe derived data can be considered to construct degradation kinetics based on carboxyl content variation versus time.

Keywords: hydrolytic degradation, physical ageing, poly(butylene succinate), polyester

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Authors: Javad Sadidi, Ehsan Babaei, Hani Rezayan

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The advent of web 2.0 gives a possibility to scale down the costs of data collection and mapping, specifically if the process is done by volunteers. Every volunteer can be thought of as a free and ubiquitous sensor to collect spatial, descriptive as well as multimedia data for tourist services. The lack of large-scale information, such as real-time climate and weather conditions, population density, and other related data, can be considered one of the important challenges in developing countries for tourists to make the best decision in terms of time and place of travel. The current research aims to design and implement a spatiotemporal web map service using volunteer-submitted data. The service acts as a tourist-guide service in which tourists can search interested places based on their requested time for travel. To design the service, three tiers of architecture, including data, logical processing, and presentation tiers, have been utilized. For implementing the service, open-source software programs, client and server-side programming languages (such as OpenLayers2, AJAX, and PHP), Geoserver as a map server, and Web Feature Service (WFS) standards have been used. The result is two distinct browser-based services, one for sending spatial, descriptive, and multimedia volunteer data and another one for tourists and local officials. Local official confirms the veracity of the volunteer-submitted information. In the tourist interface, a spatiotemporal search engine has been designed to enable tourists to find a tourist place based on province, city, and location at a specific time of interest. Implementing the tourist-guide service by this methodology causes the following: the current tourists participate in a free data collection and sharing process for future tourists, a real-time data sharing and accessing for all, avoiding a blind selection of travel destination and significantly, decreases the cost of providing such services.

Keywords: VGI, tourism, spatiotemporal, browser-based, web mapping

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Authors: Tarcisio F. Leao, Bruno Utiyama, Jeison Fonseca, Eduardo Bock, Aron Andrade

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This work presents a blood flow estimator based in Look-Up-Table (LUT) for control of Left Ventricular Assist Device (LVAD). This device has been used as bridge to transplantation or as destination therapy to treat patients with heart failure (HF). Destination Therapy application requires a high performance LVAD; thus, a stable control is important to keep adequate interaction between heart and device. LVAD control provides an adequate cardiac output while sustaining an appropriate flow and pressure blood perfusion, also described as physiologic control. Because thrombus formation and system reliability reduction, sensors are not desirable to measure these variables (flow and pressure blood). To achieve this, control systems have been researched to estimate blood flow. LVAD used in the study is composed by blood centrifugal pump, control, and power supply. This technique used pump and actuator (motor) parameters of LVAD, such as speed and electric current. Estimator relates electromechanical torque (motor or actuator) and hydraulic power (blood pump) via LUT. An in vitro Mock Loop was used to evaluate deviations between blood flow estimated and actual. A solution with glycerin (50%) and water was used to simulate the blood viscosity with hematocrit 45%. Tests were carried out with variation hematocrit: 25%, 45% and 58% of hematocrit, or 40%, 50% and 60% of glycerin in water solution, respectively. Test with bovine blood was carried out (42% hematocrit). Mock Loop is composed: reservoir, tubes, pressure and flow sensors, and fluid (or blood), beyond LVAD. Estimator based in LUT is patented, number BR1020160068363, in Brazil. Mean deviation is 0.23 ± 0.07 L/min for mean flow estimated. Larger mean deviation was 0.5 L/min considering hematocrit variation. This estimator achieved deviation adequate for physiologic control implementation. Future works will evaluate flow estimation performance in control system of LVAD.

Keywords: blood pump, flow estimator, left ventricular assist device, look-up-table

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Authors: Somnath Bhattacharya, Kamal Sharma, Vaibhav Sonkar

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Composite materials emerged in the middle of the 20th century as a promising class of engineering materials providing new prospects for modern technology. Recently, a new class of composite materials known as functionally graded materials (FGMs) has drawn considerable attention of the scientific community. In general, FGMs are defined as composite materials in which the composition or microstructure or both are locally varied so that a certain variation of the local material properties is achieved. This gradual change in composition and microstructure of material is suitable to get gradient of properties and performances. FGMs are synthesized in such a way that they possess continuous spatial variations in volume fractions of their constituents to yield a predetermined composition. These variations lead to the formation of a non-homogeneous macrostructure with continuously varying mechanical and / or thermal properties in one or more than one direction. Lightweight functionally graded composites with high strength to weight and stiffness to weight ratios have been used successfully in aircraft industry and other engineering applications like in electronics industry and in thermal barrier coatings. In the present work, elastic-plastic crack growth problems (using Ramberg-Osgood Model) in an FGM plate under cyclic load has been explored by extended finite element method. Both edge and centre crack problems have been solved by taking additionally holes, inclusions and minor cracks under plane stress conditions. Both soft and hard inclusions have been implemented in the problems. The validity of linear elastic fracture mechanics theory is limited to the brittle materials. A rectangular plate of functionally graded material of length 100 mm and height 200 mm with 100% copper-nickel alloy on left side and 100% ceramic (alumina) on right side is considered in the problem. Exponential gradation in property is imparted in x-direction. A uniform traction of 100 MPa is applied to the top edge of the rectangular domain along y direction. In some problems, domain contains major crack along with minor cracks or / and holes or / and inclusions. Major crack is located the centre of the left edge or the centre of the domain. The discontinuities, such as minor cracks, holes, and inclusions are added either singly or in combination with each other. On the basis of this study, it is found that effect of minor crack in the domain’s failure crack length is minimum whereas soft inclusions have moderate effect and the effect of holes have maximum effect. It is observed that the crack growth is more before the failure in each case when hard inclusions are present in place of soft inclusions.

Keywords: elastic-plastic, fatigue crack, functionally graded materials, extended finite element method (XFEM)

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Authors: Elizaveta Petelina, Anton Sizo

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Environmental remediation projects deal with a wide spectrum of data, including data collected during site assessment, execution of remediation activities, and environmental monitoring. Therefore, an appropriate data management is required as a key factor for well-grounded decision making. The Environmental Data Management System (EDMS) was developed to address all necessary data management aspects, including efficient data handling and data interoperability, access to historical and current data, spatial and temporal analysis, 2D and 3D data visualization, mapping, and data sharing. The system focuses on support of well-grounded decision making in relation to required mitigation measures and assessment of remediation success. The EDMS is a combination of enterprise and desktop level data management and Geographic Information System (GIS) tools assembled to assist to environmental remediation, project planning, and evaluation, and environmental monitoring of mine sites. EDMS consists of seven main components: a Geodatabase that contains spatial database to store and query spatially distributed data; a GIS and Web GIS component that combines desktop and server-based GIS solutions; a Field Data Collection component that contains tools for field work; a Quality Assurance (QA)/Quality Control (QC) component that combines operational procedures for QA and measures for QC; Data Import and Export component that includes tools and templates to support project data flow; a Lab Data component that provides connection between EDMS and laboratory information management systems; and a Reporting component that includes server-based services for real-time report generation. The EDMS has been successfully implemented for the Project CLEANS (Clean-up of Abandoned Northern Mines). Project CLEANS is a multi-year, multimillion-dollar project aimed at assessing and reclaiming 37 uranium mine sites in northern Saskatchewan, Canada. The EDMS has effectively facilitated integrated decision-making for CLEANS project managers and transparency amongst stakeholders.

Keywords: data management, environmental remediation, geographic information system, GIS, decision making

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Authors: Abdul Hadi Butt, Asfandyar Arshad

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The purpose of this paper is to study the thrust variation in different configurations of clustered nozzles. It involves the design and analysis of clustered configuration of nozzles using Ansys fluent. Clustered nozzles with different configurations are simulated and compared on basis of effective exhaust thrust. Mixing length for the flow interaction is also calculated. Further clustered configurations are analyzed over different altitudes. An optimum value of the thrust among different configurations is proposed at the end of comparisons.

Keywords: CD nozzle, cluster, thrust, fluent, ANSYS

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Authors: Ola Hall, Ibrahim Wahab, Thorsteinn Rognvaldsson, Mattias Ohlsson

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The subfield of poverty and welfare estimation that applies machine learning tools and methods on satellite imagery is a nascent but rapidly growing one. This is in part driven by the sustainable development goal, whose overarching principle is that no region is left behind. Among other things, this requires that welfare levels can be accurately and rapidly estimated at different spatial scales and resolutions. Conventional tools of household surveys and interviews do not suffice in this regard. While they are useful for gaining a longitudinal understanding of the welfare levels of populations, they do not offer adequate spatial coverage for the accuracy that is needed, nor are their implementation sufficiently swift to gain an accurate insight into people and places. It is this void that satellite imagery fills. Previously, this was near-impossible to implement due to the sheer volume of data that needed processing. Recent advances in machine learning, especially the deep learning subtype, such as deep neural networks, have made this a rapidly growing area of scholarship. Despite their unprecedented levels of performance, such models lack transparency and explainability and thus have seen limited downstream applications as humans generally are apprehensive of techniques that are not inherently interpretable and trustworthy. While several studies have demonstrated the superhuman performance of AI models, none has directly compared the performance of such models and human readers in the domain of poverty studies. In the present study, we directly compare the performance of human readers and a DL model using different resolutions of satellite imagery to estimate the welfare levels of demographic and health survey clusters in Tanzania, using the wealth quintile ratings from the same survey as the ground truth data. The cluster-level imagery covers all 608 cluster locations, of which 428 were classified as rural. The imagery for the human readers was sourced from the Google Maps Platform at an ultra-high resolution of 0.6m per pixel at zoom level 18, while that of the machine learning model was sourced from the comparatively lower resolution Sentinel-2 10m per pixel data for the same cluster locations. Rank correlation coefficients of between 0.31 and 0.32 achieved by the human readers were much lower when compared to those attained by the machine learning model – 0.69-0.79. This superhuman performance by the model is even more significant given that it was trained on the relatively lower 10-meter resolution satellite data while the human readers estimated welfare levels from the higher 0.6m spatial resolution data from which key markers of poverty and slums – roofing and road quality – are discernible. It is important to note, however, that the human readers did not receive any training before ratings, and had this been done, their performance might have improved. The stellar performance of the model also comes with the inevitable shortfall relating to limited transparency and explainability. The findings have significant implications for attaining the objective of the current frontier of deep learning models in this domain of scholarship – eXplainable Artificial Intelligence through a collaborative rather than a comparative framework.

Keywords: poverty prediction, satellite imagery, human readers, machine learning, Tanzania

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Authors: C. Bejrananda, Y. Lee, T. Khamkaew

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With the rise of the importance of air transportation in the 21st century, the role of economics in airport planning and decision-making has become more important to the urban structure and land value around it. Therefore, this research aims to examine the relationship between an airport and its impacts on the distribution of urban land uses and land values by applying the Alonso’s bid rent model. The New Bangkok International Airport (Suvarnabhumi International Airport) was taken as a case study. The analysis was made over three different time periods of airport development (after the airport site was proposed, during airport construction, and after the opening of the airport). The statistical results confirm that Alonso’s model can be used to explain the impacts of the new airport only for the northeast quadrant of the airport, while proximity to the airport showed the inverse relationship with the land value of all six types of land use activities through three periods of time. It indicates that the land value for commercial land use is the most sensitive to the location of the airport or has the strongest requirement for accessibility to the airport compared to the residential and manufacturing land use. Also, the bid-rent gradients of the six types of land use activities have declined dramatically through the three time periods because of the Asian Financial Crisis in 1997. Therefore, the lesson learned from this research concerns about the reliability of the data used. The major concern involves the use of different areal units for assessing land value for different time periods between zone block (1995) and grid block (2002, 2009). As a result, this affect the investigation of the overall trends of land value assessment, which are not readily apparent. In addition, the next concern is the availability of the historical data. With the lack of collecting historical data for land value assessment by the government, some of data of land values and aerial photos are not available to cover the entire study area. Finally, the different formats of using aerial photos between hard-copy (1995) and digital photo (2002, 2009) made difficult for measuring distances. Therefore, these problems also affect the accuracy of the results of the statistical analyses.

Keywords: airport development area, economic rents, spatial pattern, suvarnabhumi international airport

Procedia PDF Downloads 275

Authors: S. Mamoucha, N. Tsafantakis, Α. Ioannidis, S. Chatzipanagiotou, C. Nikolaou, L. Skaltsounis, N. Fokialakis, N. Christodoulakis

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Introduction: Plant secondary metabolites (SM) can be grouped into three chemically distinct groups: terpenes, phenolics, and nitrogen-containing compounds. For many years the adaptive significance of SM was unknown. They were thought to be functionless end-products. Currently it is accepted that many secondary metabolites (also known as natural products) have important ecological roles in plants. For instance, they serve as attractants (odor, color, taste) for pollinators and seed-dispersing animals. Moreover, they protect plants from herbivores, microbial pathogens and from environmental stress (high and low temperatures, drought, alkalinity, salinity, radiation etc). It is well known that both biotic and abiotic stress often increase the accumulation of SM. The local climatic conditions, seasonal changes, external factors such as light, temperature, humidity affect the biosynthesis and composition of secondary metabolites. A well known dioecious evergreen plant, Pistacia lentiscus L. (mastic tree), was selected in order to study the metabolic variations occur in response to the different climate conditions, due to the seasonal variation and its effect on the biosynthesis of bioactive compounds. Materials-methods: Young and mature leaves were collected in January and July 2014, dried and extracted by accelerated solvent extraction (Dionex ASE™ 350) using solvents of increased polarity (DCM, MeOH, and H2O). GC-MS and UHPLC-HRMS analysis were carried out in order to define the nature and the relative abundance of SM. The antibacterial activity was evaluated by using the Agar Disc Diffusion Assay against ATCC and clinical isolates strains: Escherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa, Candida albicans, Streptococcus mutans and Klebsiella pneumoniae. All tests were carried out in duplicate and the average radii of the inhibition zones were calculated for each extract. Results: According to the phytochemical profile obtained from each extract, the biosynthesis of SM varied both qualitatively and quantitatively under the two different types of seasonal stress. With exception of the biologically inactive nonpolar DCM extract of July, all extracts inhibited the growth of most of the investigated microorganisms. A clear positive correlation has been observed between the relative abundance of SM and the bioactivity of the DCM extracts of January and July. Observed changes during phytochemical analysis were mainly focused on the triterpenoid content. On the other hand, the bioactivity of the polar extracts (MeOH and H2O) of January and July resulted practically invariable against most of the microorganisms, besides the significant variation of the SM content due to the seasonal variation. Conclusion: Our results clearly confirmed the hypothesis of abiotic stress as an important regulating factor that significantly affects the biosynthesis of secondary metabolites and thus the presence of bioactive compounds. Acknowledgment: This work was supported by IKY - State Scholarship Foundation, Athens, Greece.

Keywords: antibacterial screening, phytochemical profile, Pistacia lentiscus, abiotic stress

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Authors: Aschenaki Zerihun Kea, Bernt Lindtjorn, Achamyelesh Gebretsadik, Sven Gudmund Hinderaker

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Introduction: Maternal mortality studies conducted at the national level do not provide the information needed for planning and monitoring health programs at lower administrative levels. The aim of this study was to measure maternal mortality, identify risk factors and district-level variations in Sidama National Regional State, southern Ethiopia. Methods: A cross sectional population-based survey was carried out in households where women reported pregnancy and birth outcomes in the past five years. The study was conducted in the Sidama National Regional State, southern Ethiopia, from July 2019 to May 2020. Multi-stage cluster sampling technique was employed. The outcome variable of the study was maternal mortality. Complex sample logistic regression analysis was applied to assess variables independently associated with maternal mortality. Results: We registered 10602 live births (LB) and 48 maternal deaths, yielding an overall maternal mortality ratio (MMR) of 419; 95% CI: 260-577 per 100,000 LB. Aroresa district had the highest MMR with 1142 (95% CI: 693-1591) per 100,000 LB. Leading causes of death were haemorrhage 21 (41%) and eclampsia 10 (27%). Thirty (59%) mothers died during labour, or within 24 hours after delivery, 25 (47%) died at home and 17 (38%) at a health facility. Mothers who did not have formal education had a higher risk of maternal death (AOR: 4.4; 95% CI: 1.7 – 11.0). The risk of maternal death was higher in districts with a low midwife-to-population ratio (AOR: 2.9; 95% CI: 1.0-8.9). Conclusion: The high maternal mortality with district-level variations in Sidama Region highlights the importance of improving obstetric care and employing targeted interventions in areas with high mortality rates. Due attention should be given to improving access to female education. Additional midwives have to be trained and deployed to improve maternal health services and consequently save the lives of mothers.

Keywords: maternal mortality variation, maternal death, Sidama, Ethiopia

Procedia PDF Downloads 74

Authors: Marwa Elkalla, E. Ali Abdelfadil, Ali. Mohamed. M. Sami, Ali M. Abdel-Monem

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To assess the impact of the blood collection technique on clinical pathology markers and to establish reference intervals, a study was performed using normal, healthy C57BL/6 mice. Both sexes were employed, and they were randomly assigned to different groups depending on the phlebotomy technique used. The blood was drawn in one of four ways: intracardiac (IC), caudal vena cava (VC), caudal vena cava (VC) plus a peritoneal collection of any extravasated blood, or retroorbital phlebotomy (RO). Several serum biochemistries, such as a liver function test, a complete blood count with differentials, and a platelet count, were analysed from the blood and serum samples analysed. Red blood cell count, haemoglobin (p >0.002), hematocrit, alkaline phosphatase, albumin, total protein, and creatinine were all significantly greater in female mice. Platelet counts, specific white blood cell numbers (total, neutrophil, lymphocyte, and eosinophil counts), globulin, amylase, and the BUN/creatinine ratio were all greater in males. The VC approach seemed marginally superior to the IC approach for the characteristics under consideration and was linked to the least variation among both sexes. Transaminase levels showed the greatest variation between study groups. The aspartate aminotransferase (AST) values were linked with decreased fluctuation for the VC approach, but the alanine aminotransferase (ALT) values were similar between the IC and VC groups. There was a lot of diversity and range in transaminase levels between the MC and RO groups. We found that the RO approach, the only one tested that allowed for repeated sample collection, yielded acceptable ALT readings. The findings show that the test results are significantly affected by the phlebotomy technique and that the VC or IC techniques provide the most reliable data. When organising a study and comparing data to reference ranges, the ranges supplied here by collection method and sex can be utilised to determine the best approach to data collection. The authors suggest establishing norms based on the procedures used by each individual researcher in his or her own lab.

Keywords: clinical, pathology, blood, effect

Procedia PDF Downloads 97

Authors: Muhammad Yayat Afianto, Darmawan, Agung Putra Utama, Hari Kushardanto

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Fish Forever, Rare’s innovative coastal fisheries program, combined community-based conservation management approach with spatial management to restore and protect Indonesia’s small-scale fisheries by establishing Fishing Managed Access Area. A ‘TURF-Reserve’ is a fishery management approach that positions fishers at the center of fisheries management, empowering them to take care of and make decisions about the future of their fishery. After two years of the program, social marketing campaigns succeeded in changing their behavior by adopting the new conservation behavior. The Pride-TURF-R campaigns developed an overarching hypothesis of impact that captured the knowledge, attitude and behavior changes needed to reduce threats and achieve conservation results. Rare help Batu Belah fishers to develop their group, developed with their roles, sustainable fisheries plan, and the budget plan. On 12th February 2017, the Head of Loka Kawasan Konservasi Perairan Nasional (LKKPN) which is a Technical Implementation Unit for National Marine Conservation Areas directly responsible to the Directorate General for Marine Spatial Management in the Ministry of Marine Affairs and Fisheries had signed a Partnership Agreement with the Head of Batu Belah Village to manage a TURF+Reserve area as wide as 909 hectares. The fishers group have been collecting the catch and submitting the report monthly, initiated the installation of the buoy markers for the No Take Zone, and formed the Pokmaswas (community-based surveillance group). Prior to this behavior adoption, they don’t have any fisheries data, no group of fishers, and they have still fishing inside the No Take Zone. This is really a new behavior adoption for them. This paper will show the process and success story of the social marketing campaign to conserve marine habitat in Anambas through Pride-TURF-R program.

Keywords: behavior adoption, community participation, no take zone, pride-TURF-R

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Authors: U. Ali Rahoma, Nabil Esawy, Fawzia Ibrahim Moursy, A. H. Hassan, Samy A. Khalil, Ashraf S. Khamees

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The design of any solar energy conversion system requires the knowledge of solar radiation data obtained over a long period. Satellite data has been widely used to estimate solar energy where no ground observation of solar radiation is available, yet there are limitations on the temporal coverage of satellite data. Reanalysis is a “retrospective analysis” of the atmosphere parameters generated by assimilating observation data from various sources, including ground observation, satellites, ships, and aircraft observation with the output of NWP (Numerical Weather Prediction) models, to develop an exhaustive record of weather and climate parameters. The evaluation of the performance of reanalysis datasets (ERA-5) for North Africa against high-quality surface measured data was performed using statistical analysis. The estimation of global solar radiation (GSR) distribution over six different selected locations in North Africa during ten years from the period time 2011 to 2020. The root means square error (RMSE), mean bias error (MBE) and mean absolute error (MAE) of reanalysis data of solar radiation range from 0.079 to 0.222, 0.0145 to 0.198, and 0.055 to 0.178, respectively. The seasonal statistical analysis was performed to study seasonal variation of performance of datasets, which reveals the significant variation of errors in different seasons—the performance of the dataset changes by changing the temporal resolution of the data used for comparison. The monthly mean values of data show better performance, but the accuracy of data is compromised. The solar radiation data of ERA-5 is used for preliminary solar resource assessment and power estimation. The correlation coefficient (R2) varies from 0.93 to 99% for the different selected sites in North Africa in the present research. The goal of this research is to give a good representation for global solar radiation to help in solar energy application in all fields, and this can be done by using gridded data from European Centre for Medium-Range Weather Forecasts ECMWF and producing a new model to give a good result.

Keywords: solar energy, solar radiation, ERA-5, potential energy

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Authors: Sabir Hussain, Muhammad Naeem, Yousif Aldryhim, Susan E. Halbert, Qingjun Wu

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Plant viruses annually cause severe economic losses in crop production and globally, different aphid species are responsible for the transmission of such viruses. Additionally, aphids are also serious pests of trees, and agricultural crops. Al Bahah Province, Kingdom of Saudi Arabia (KSA) has a high native and introduced plant species with a temperate climate that provides ample habitats for aphids. In this study, we surveyed virus-transmitting aphids from the Province to highlight their spatial distributions and hot spot areas for their target control strategies. During our fifteen month's survey in Al Bahah Province, three hundred and seventy samples of aphids were collected using both beating sheets and yellow water pan traps. Consequently, fifty-four aphid species representing 30 genera belonging to four families were recorded from Al Bahah Province. Alarmingly, 35 aphid species from our records are virus transmitting species. The most common virus transmitting aphid species based on number of collecting samples, were Macrosiphum euphorbiae (Thomas, 1878), Brachycaudus rumexicolens (Patch, 1917), Uroleucon sonchi (Linnaeus, 1767), Brachycaudus helichrysi (Kaltenbach, 1843), and Myzus persicae (Sulzer, 1776). The numbers of samples for the forementioned species were 66, 24, 23, 22, and 20, respectively. The widest range of plant hosts were found for M. euphorbiae (39 plant species), B. helichrysi (12 plant species), M. persicae (12 plant species), B. rumexicolens (10 plant species), and U. sonchi (9 plant species). The hottest spot areas were found in Al-Baha, Al Mekhwah and Biljarashi cities of the province on the basis of their abundance. This study indicated that Al Bahah Province has relatively rich aphid diversity due to the relatively high plant diversity in a favorable climatic condition. ArcGIS tools can be helpful for biologists to implement the target control strategies against these pests in the integrated pest management, and ultimately to save money and time.

Keywords: Al Bahah province, aphid-virus interaction, biodiversity, global information system

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Authors: Eric Bang

Abstract:

Interactions between receptors and ligands are crucial for many essential biological processes, including neurotransmission and metabolism. Ligand-receptor analyses that examine cell behavior and interactions often utilize cell type-specific RNA expressions from single-cell RNA sequencing (scRNA-seq) data. Using CellPhoneDB, a public repository consisting of ligands, receptors, and ligand-receptor interactions, the cell-cell interactions were explored in a specific scRNA-seq dataset from kidney tissue and portrayed the results with dot plots and heat maps. Depending on the type of cell, each ligand-receptor pair was aligned with the interacting cell type and calculated the positori probabilities of these associations, with corresponding P values reflecting average expression values between the triads and their significance. Using single-cell data (sample kidney cell references), genes in the dataset were cross-referenced with ones in the existing CellPhoneDB dataset. For example, a gene such as Pleiotrophin (PTN) present in the single-cell data also needed to be present in the CellPhoneDB dataset. Using the single-cell transcriptomics data via slide-seq and reference data, the CellPhoneDB program defines cell types and plots them in different formats, with the two main ones being dot plots and heat map plots. The dot plot displays derived measures of the cell to cell interaction scores and p values. For the dot plot, each row shows a ligand-receptor pair, and each column shows the two interacting cell types. CellPhoneDB defines interactions and interaction levels from the gene expression level, so since the p-value is on a -log10 scale, the larger dots represent more significant interactions. By performing an interaction analysis, a significant interaction was discovered for myeloid and T-cell ligand-receptor pairs, including those between Secreted Phosphoprotein 1 (SPP1) and Fibronectin 1 (FN1), which is consistent with previous findings. It was proposed that an effective protocol would involve a filtration step where cell types would be filtered out, depending on which ligand-receptor pair is activated in that part of the tissue, as well as the incorporation of the CellPhoneDB data in a streamlined workflow pipeline. The filtration step would be in the form of a Python script that expedites the manual process necessary for dataset filtration. Being in Python allows it to be integrated with the CellPhoneDB dataset for future workflow analysis. The manual process involves filtering cell types based on what ligand/receptor pair is activated in kidney cells. One limitation of this would be the fact that some pairings are activated in multiple cells at a time, so the manual manipulation of the data is reflected prior to analysis. Using the filtration script, accurate sorting is incorporated into the CellPhoneDB database rather than waiting until the output is produced and then subsequently applying spatial data. It was envisioned that this would reveal wherein the cell various ligands and receptors are interacting with different cell types, allowing for easier identification of which cells are being impacted and why, for the purpose of disease treatment. The hope is this new computational method utilizing spatially explicit ligand-receptor association data can be used to uncover previously unknown specific interactions within kidney tissue.

Keywords: bioinformatics, Ligands, kidney tissue, receptors, spatial transcriptome

Procedia PDF Downloads 142